The National Consortium for Data Science

2025 NCDS Fall Career Panel: Analyzing Data Science Careers
2025-10-01 18:00 - 19:00 (America/New_York) | via Zoom
Join panelists working in a variety of fields, leveraging their knowledge and experience in data science to forge distinct careers in data science. The journey looks different for everyone, but a dream job is the destination. We’ll discuss a few examples of what it takes to get there. We’ll also dive into the hard and soft skills that make a top candidate the only candidate for a role in this competitive field. Get ready to dive into the following topics:

Do I need a graduate degree to be competitive?
What are three things I should do as an undergrad to make my resume stand out?
HELP! I don’t have a degree in data science!

Moderator: Sarah Egan Warren, Teaching Assistant Professor, Institute for Advanced Analytics and Lead Facilitator, UNC System’s Faculty Learning Community for AI in Teaching & Learning, North Carolina State University
Panelists:

Laura Faircloth, Arabic NLP Scientist, MetaMetrics
Emily Hadley, Security Researcher, Microsoft AI Red Team
Ben Heller, GenAI Transformation Lead, Google Cloud
Vrushali Sawant, Data Scientist, Data Ethics Practice, SAS

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Foundations of AI: Intro to Generative AI for Non-Coders
2025-09-24 13:00 - 17:00 | via Zoom
This four-hour workshop is designed to provide non-technical audiences an understanding of AI, its fundamental concepts, and its practical applications. The course clarifies technical jargon and reveals how everyday people rely on AI in their personal and professional lives.

Attendees will receive big picture explanations of how AI works and will learn about opportunities and risks in the field.
They will leave the course with deeper awareness of AI use in their work environment and a greater technical understanding of how AI drives innovation across sectors.
Attendees will also learn the basics of prompt engineering, with examples on how to get the best outputs from generative AI tools by learning best practices in prompt engineering.

Prerequisites: None! This course is open and encouraged for anyone and everyone.
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NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: Intro to Generative AI for Non-Coders on Wednesday, Sept. 24 from 1 p.m. – 5 p.m. ET.
To apply for a full scholarship, submit your application via this form. DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

DataBytes: Introducing the NCATS Biomedical Data Translator: A new tool for Biomedical Data Integration and Inference
2025-08-27 12:00 - 13:00
Speaker: Chris Bizon, Director of Analytics and Data Science, RENCI
Host: Becky Boyles, Deputy Director, RENCI
The growing availability of biomedical data offers vast potential to improve human health, but the complexity and lack of integration of these datasets often limit their utility. To address this, the Biomedical Data Translator Consortium has developed an open-source knowledge graph–based system—Translator—designed to integrate, harmonize, and make inferences over diverse biomedical data sources. To demonstrate Translator’s application and impact, we highlight features of the user interface in the context of three real-world use cases: suggesting potential therapeutics for patients with rare disease; explaining the mechanism of action of a pipeline drug; and screening and validating drug candidates in a model organism.
Key takeaways include the following:

Based on rich concept modeling and deep provenance tracking, we’ll provide an overview of how Translator works.
Opportunities to engage with Translator at http://ui.transltr.io and through our Ambassadors and Champions program.

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Chris Bizon | bizon@renci.org
Chris Bizon is the director of Analytics and Data Science. He leads a team that applies a range of analytical methods including knowledge graphs, machine learning, visual analytics, semantic web-based reasoning, and textual annotation across many domains. He joined RENCI in 2008 as a member of the informatics group, where he worked in the areas of high-throughput sequencing, genomic analysis, and clinical genomics. Prior to joining RENCI, he spent a decade in the private sector working as both a developer and a researcher in the areas of fluid dynamics simulations and the application of machine learning to drug discovery. He holds a BS in Physics from the University of North Carolina at Chapel Hill and a PhD in Physics from the University of Texas at Austin, where he developed numerical models of nonlinear phenomena including pattern formation in oscillated granular media.

DataBytes: The AI Security Gap: How Close Are We to Achieving Trustworthy AI?
2025-06-11 12:00 - 13:30 | via Zoom
Key Findings from the NIST AI 100-2 Report
In this webinar, Apostol Vassilev will examine the recently published 2025 edition of the NIST Al 100-2 report, a crucial resource for organizations seeking to ensure the security of Al systems. The talk will focus on the security of generative Al models, tailored to address the needs of Al practitioners and stakeholders in the audience. The report provides a comprehensive taxonomy of concepts and terminology in the field of adversarial machine learning (AML), organizing key Al technologies, attack life cycle stages, and attacker goals, objectives, capabilities, and knowledge into a conceptual hierarchy. By identifying current security challenges in the Al system life cycle and describing methods for mitigation and management, the report aims to establish a common language for the rapidly evolving AML landscape. This webinar will provide attendees with a deeper understanding of the development and deployment of more trustworthy and responsible Al systems.
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Foundations of AI: The Basics of Natural Language Processing
2025-05-15 13:00 - 17:00 | via Zoom
In this workshop you’ll learn the basics of Natural Language Processing (NLP): the subfield of AI and data science dedicated to human language.
You’ll also learn:

How to do basic analyses with unstructured text data
How to use deep learning to create NLP models from scratch and finally how
How large language models (LLMs) and Generative AI work and connect to other NLP skills.

We’ll touch on some aspects of deep learning that are specific to NLP, some more basic analyses of unstructured data and how to deal with lots of unlabeled text (e.g. clustering) and basically go deeper on things that are really NLP-related as opposed to AI more generally.
Pre-requisites
Basic Python knowledge required, machine learning knowledge helpful but not required, very basic data science knowledge (i.e. linear regression) is recommended.
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Scholarship Information
NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: The Basics of Natural Language Processing course on Thursday, May 15, 2025 from 1:00 p.m. – 5:00 p.m. ET.

To apply for a full scholarship, submit your application via this form.
DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

DataBytes: Do Large Language Models Have a Legal Duty to Tell the Truth?
2025-04-24 12:00 - 13:00
Large language models (LLMs) do not distinguish between fact and fiction. They will return an answer to almost any prompt, yet factually incorrect responses are commonplace. Our tendency to anthropomorphise machines and trust models as human-like truth tellers — consuming and spreading the bad information that they produce in the process — is uniquely worrying. They are not, strictly speaking, designed to tell the truth.
Yet they are implemented in many sectors where truth and detail matter such as education, science, health, the media, law, and finance. Our guest presenter Sandra Wachter coined the idea of “careless speech” as a new type of harm created by large language models (LLM) that poses cumulative, long-term risks to science, education, and shared social truth in democratic societies. These subtle mistruths are poised to cumulatively degrade and homogenize knowledge over time.
This begs the question: Do large language models have a legal duty to tell the truth?
Join us as Sandra shows the prevalence of hallucinations, and we assess the existence of truth-related obligations in EU human rights law and the Artificial Intelligence Act, Digital Services Act, Product Liability Directive and Artificial Intelligence Liability Directive. We will close by proposing ideas of how to reduce hallucinations in LLMs and a robust Q & A opportunity.
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Foundations of AI: Intro to Generative AI for Coders
2025-03-20 17:00 - 21:00
This course will give you an overview of what Generative AI is and how it works, and how to do some basic tasks in Generative AI. You’ll learn some tips and tricks for prompt engineering and prompt tuning, as well as more advanced techniques like RAG, fine-tuning and how to evaluate generative model performance. By the end of the course you should have enough knowledge to combine open-source LLMs with a more targeted dataset to efficiently handle AI tasks that are relevant to your work.
Prerequisites
Understanding basic Python and the very basics of data science (i.e., what data looks like in a csv format and how to do a simple linear regression) would be helpful in this class. Understanding machine learning basics is good, but not required.
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Scholarship Information
NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: Intro to Generative AI for Coders course on Thursday, Mar. 20, 2025 from 5:00 p.m. – 9:00 p.m. ET.

To apply for a full scholarship, submit your application via this form.
DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

Foundations of AI: Intro to AI and Deep Learning
2025-02-20 13:00 - 17:00
In this course you’ll learn about Artificial Intelligence (AI), starting with foundational concepts in machine learning and deep learning, then moving to the basics of Natural Language Processing and Computer Vision that got us to our current boom in Generative AI as demonstrated by GPT-3, DALL-E and other well-known tools. Learn how to train your own AI models, and how to make the most of open-source and pre-trained models on the market.

How machine learning works
Basics of deep learning
Basics of Natural Language Processing
How to do deep learning with language data

Prerequisites
Understanding basic Python and the very basics of data science (i.e., what data looks like in a csv format and how to do a simple linear regression) would be helpful in this class. Understanding machine learning basics is good, but not required.
Register for Course
Scholarship Information
NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: AI for Non Coders course on Thursday, Feb. 20 from 1:00 p.m. – 5:00 p.m. ET.

To apply for a full scholarship, submit your application via this form.
DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

2025 NCDS Spring Career Panel: Analyzing Data Science Careers
2025-02-05 17:00 - 18:00
Join panelists working in a variety of fields, leveraging their knowledge and experience in data science to forge distinct careers in data science. The journey looks different for everyone, but a dream job is the destination. We’ll discuss a few examples of what it takes to get there. We’ll also dive into the hard and soft skills that make a top candidate the only candidate for a role in this competitive field. Get ready to dive into the following topics:

Do I need a graduate degree to be considered for my dream job?
What are three things I can do to stand out from the competition?
HELP! I don’t have a degree in data science!

Register for the Event

Careers in Data Science: Rock Your LinkedIn Profile with Becky Brown
2025-01-29 12:00 - 13:00 | via Zoom
Your presence on LinkedIn and other social channels is the first impression you make on clients and your network. Creating the right presence is the key to having people “opt-in” to conversations with you. Join this session to learn how to articulate a clear and authentic personal brand, how to define your LinkedIn strategy, and how to build a LinkedIn profile that connects with your target audience so you can make more authentic connections.
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About the Speaker | Becky Brown
Becky Brown brings almost four decades of experience into her work as a coach, trainer, and LinkedIn content creator. Her career spans a blend of sales and marketing roles in the technology field and she currently works to support her colleagues as senior sales enablement program manager at the largest privately-held software company in the role. She focuses on helping professionals find greater fulfillment in work and life by expanding their insights and perspectives through meaningful social connections. Becky earned a Business degree from Meredith College and holds certifications in LinkedIn coaching, social selling, career coaching and professional life coaching.

DataBytes: Intro to NLP, LLMs and more - a Taste of Foundations of AI
2024-12-12 12:00 - 13:00
In this short session you’ll learn the basics of Natural Language Processing, starting with turning words and sentences into embeddings for use in deep learning tasks, as well as an intro to language models, large and otherwise. You’ll learn some hands-on tips and tricks for making sense of language data, and get a technical but beginner-friendly introduction to the wide world of AI with language.
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DataBytes: Navigating the Data Divide: Approaching Analytics Across Organizational Maturity Levels
2024-10-17 12:00 - 13:00
Organizations at varying levels of analytical maturity are increasingly seeking to optimize their data usage. This presentation, delivered by two experienced data scientists, will discuss how analytics can vary across different environments. The speakers will draw on their work with clients across the analytical maturity spectrum, highlighting their efforts to enhance analytically established organizations and develop capabilities in analytically emerging ones. They will examine a range of analytical methodologies and how these can either support or hinder organizational performance. This presentation will focus on how different organizations engage with analytics based on their maturity levels, outlining the specific opportunities and challenges each faces. The goal is to provide attendees with practical insights on how different organizations approach data analytics so that they can be prepared to make analytic contributions at any organization.
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2024 NCDS Fall Career Panel: Analyzing Data Science Careers
2024-10-09 17:00 - 18:00
You don’t want to miss these data science professionals provide insight into what it takes to capture the attention of top recruiters in data science and data analytics. Our panelists represent a variety of career stages and they are ready to discuss what it takes to set yourself apart as you launch your career search.
During our fall event, you’ll join panelists working in data and Al security, human movement analysis in research and clinical labs, and more as they explore the paths that lead to a career in data science. The journey looks different for everyone, but a dream job is the destination. We’ll discuss a few examples of what it takes to get there and dive into the hard and soft skills that make a top candidate the only candidate for a role in this competitive field.
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Foundations of AI: AI for Non-Coders
2024-09-26 13:00 - 17:00
Ever say to yourself: what even is an LLM? How do I get from chatting with ChatGPT to talking about larger AI products? How do I answer these nonstop questions from colleagues, customers, leadership and more in this new landscape?
Do you find yourself needing expertise on AI that, quite frankly, you didn’t sign up for?
This course is designed to meet the needs of people who are not necessarily well-versed in math and science but who know that they need to know the basics about AI in this changing landscape.
You’ll learn about what AI can accomplish, the intuitions behind how it works (no math or coding necessary!), and opportunities and risks. You’ll come away feeling confident that you know not only what an LLM actually is, but understand all the jargon people use to talk about it.
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Scholarship Information
NCDS is pleased to offer a limited number of full scholarships for faculty, staff and students at two-year and four-year institutions to attend the Foundations of AI: AI for Non Coders course on Thursday, Sept. 26 from 1:00 p.m. – 5:00 p.m. ET.
To apply for a full scholarship, submit your application via this form. DO NOT USE THE MAIN REGISTRATION FORM TO APPLY FOR THE SCHOLARSHIP.

Scaling Up: Developing a Coordinating Hub for Data Competency
2024-09-17 12:00 - 13:00
In this session, Dr. Crista Arangala will introduce Elon University’s Data Nexus. The Data Nexus initiative was created as part of a five-year Quality Enhancement Plan developed during its most recent accreditation process and serves as a coordinating hub for data competency initiatives at the university throughout the plan and beyond. In its first year, Data Nexus has been focused on assessing foundational technology and statistical competency of all of Elon University’s undergraduate students. Through Data Nexus, Elon University has also created a process for faculty across the institution to apply for courses to be designated as Data-Intensive and has introduced a new Micro-credential in Advanced Data Competency. Data Nexus also offers a variety of programming across campus including data camps, workshops, and data challenges. Data Nexus also offers grants to support faculty, staff, and student data-driven initiatives. In year two, Data Nexus will continue to develop curricular and co-curricular data-intensive experiences for the general Elon University undergraduate student body.
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About Dr. Crista Arangala
Dr. Crista Arangala is the Director of Elon University’s Data Nexus and Professor of Mathematics. The Data Nexus initiative was created as part of a five-year Quality Enhancement Plan developed during its most recent accreditation process and serves as a coordinating hub for data competency initiatives at the university throughout the plan and beyond. Dr. Arangala has a PhD in mathematics from the University of Cincinnati and a Masters in Higher Education from Stony Brook University. She has been at Elon University in North Carolina for 24 years, researching in a variety of fields including inverse problems, applied partial differential equations, applied linear algebra, mathematical modeling, and service-learning education. Dr. Arangala has a special interest in inquirydiscovery learning and ran a traveling science museum with her Elon University students in Kerala, India for 9 years. Dr. Arangala was chosen to be a Fulbright Scholar in 2014 as a visiting lecturer at the University of Colombo where she continued her projects in inquiry learning in Linear Algebra and began working with a modeling team focusing on Dengue fever research. Dr. Arangala has published several textbooks that implores inquiry learning techniques including Exploring Linear Algebra: Labs and Projects with Matlab and Mathematical Modeling: Branching Beyond Calculus. Her latest text, Linear Algebra with Machine Learning and Data, connects her teaching interests of infusing data into the mathematical curriculum and her research interests in applied linear algebra.

Careers in Data Science: Measuring Social Impact at the Kennedy Center
2024-09-11 18:00 - 19:00
From liberal arts major to major impact
What do Musical Theater, Psychology, History, and Business Administration all have in common? These fields can all provide you with successful tools and experiences that can lead to valuable careers incorporating data science. In this session, Trés McMichael, Senior Program Manager for Social Impact Civic Alliances at the Kennedy Center in Washington, D.C., will discuss his pathways from a liberal arts education to a non-profit professional who has incorporated research, evaluation, and data visualization as a tool to support arts, culture, and community change.
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About Trés McMichael
Trés McMichael is a joy-filled arts leader and performer who is passionate about community empowerment, arts education, and social justice. Originally from Baltimore, Trés is an alumnus of Elon University, where he graduated with degrees in Music Theatre (BFA) and Arts Administration (BA). He also holds an MFA in Arts Leadership and a certificate in Fundraising Leadership from Seattle University. While pursuing his graduate degree, he was named an EDI Research Fellow with the Association of Arts Administration Educators. He has worked with various nonprofit and arts organizations such as Arena Stage, DC Collaborative, and the NAACP. Through his work, Trés strives to do work that is in and with, not to or for, the communities he serves.

DataBytes: Data Viz, Chemistry, Art, and Public Health: Making Sense of Street Drugs
2024-08-29 12:00 - 13:00
At the Street Drug Analysis Lab, researchers analyze street drug samples from around the country and have detected about 300 unique chemical substances. But making sense of chemicals is a notorious challenge, with long names, esoteric molecules, and overlapping pharmacological properties. Therefore, the team created a flexible ontology that can adapt over time, and developed visualizations to bring order to the chaos. Using a type of chord diagram called hierarchical edge bundling (.js package), they conceptualized co-occurrence of substances in the drug supply based on 6,000 drug samples from 34 US states, showing connections between classes of molecules. Working with a local graphic designer, hand drawn illustrations highlight particularly dangerous combinations of substances and tell the story of where the samples came from.
Join team members Nabarun Dasgupta and Anuja Panthari at the intersection of chemistry, art, public health, and data science, as they describe how their project brings order to the unruly illicit drug supply. The key message: The drug supply is vast, but it is knowable.
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About the Speakers
Nabarun Dasgupta
Nabarun Dasgupta, PhD, MPH, is a scientist who studies drugs and infectious diseases. His passion is telling true stories about health with numbers. Centered in pharmaco-epidemiology, his work amplifies community and patient voices in public health. Since 2002 he has done pioneering work in pain management, opioid overdose prevention, and addiction treatment. He also has deep expertise in health informatics and machine learning. In 2023 he was honored by being placed on the TIME100 Next list of rising global leaders.
As an applied epidemiologist, Dasgupta has served as an advisor to the US Food and Drug Administration (FDA), Centers for Disease Control and Prevention (CDC), and World Health Organization (WHO). Operating with an appreciation for the social determinants and of health, he is committed to countering the impacts of racist drug policies. At UNC IPRC, he works at the Opioid Data Lab (OpioidData.org). His street drug analysis lab tests community-donated samples from around the country to figure out what lurks in the drug supply. Dasgupta co-founded two pioneering non-profit organizations. Project Lazarus in Wilkes County (North Carolina) was hailed by the Obama White House as a model for community-based overdose prevention. Remedy Alliance For The People is a groundbreaking national non-profit bulk distributor of free and low-cost naloxone to harm reduction programs. Previously he was the Chief Science Officer of Epidemico, a health informatics startup he co-founded using technology developed at Harvard Medical School. He is also an associate editor at the American Journal of Public Health.
Dasgupta earned degrees from Princeton University (molecular biology), Yale University (epidemiology of microbial diseases), and the University of North Carolina (pharmacoepidemiology). Follow him on Twitter (@nabarund).
Anuja Parathi
Anuja Panthari is an MPH Data Science candidate at UNC Gillings School of Public Health. She completed her BS in Cognitive Science and Statistics from UC Santa Cruz in 2022. Under the guidance of Dr. Dasgupta, she has been involved in harm reduction research at the Street Drug Analysis lab, assisting with multiple cutting-edge data analytics and visualization projects that will help communities demystify the street drug supply.

Data Matters 2024
2024-08-05 - 2024-08-09
Data Matters™ is a week-long series of one and two-day courses aimed at students and professionals in business, research, and government. The short course series is sponsored by the Odum Institute for Research in Social Science at UNC-Chapel Hill, the National Consortium for Data Science, and RENCI. Data Matters gives students the chance to learn about a wide range of topics in data science, analytics, visualization, curation, and more from expert instructors.
Registration is now open for the Data Matters series which will be held August 5 – 9, 2024. Register here.

DataBytes: Using GenAI to win STTR and SBIR Government Grants
2024-06-20 16:00 - 17:00
Through a competitive awards-based program, STTR and SBIR federal grants enable small businesses to explore their technological potential and open new opportunities to profit from its commercialization. However, it can be difficult for first-time applicants to get their foot in the door, between sorting through guidelines, requirements, and deadlines, and trying to locate successful examples. GrantScout is automating grant search, writing, and submission. The tool uses traditional deep learning methods and generative AI to unlock funding for everyone. Join GrantScout founders Felicia Chen and Jennifer Tang as they present how the government provides over two million grants for small businesses, the ways that their team fine-tunes their own models to create strong technical proposals, and lessons they’ve learned from past experiences that helped them build the platform.
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Foundations of AI: Intro to AI with Amy Hemmeter
2024-05-16 13:00 - 17:00
In this half-day course, you’ll learn about Artificial Intelligence (AI), starting with foundational concepts in machine learning and deep learning, then moving to the basics of Natural Language Processing and Computer Vision that got us to our current boom in Generative AI as demonstrated by GPT-3, DALL-E and other well-known tools. Learn how to train your own AI models, how to make the most of open-source and pre-trained models on the market, and how to stay ahead of the curve on technical improvements.
In this course you’ll learn:

Basics of deep learning with language data
How BERT and GPT work
What is Generative AI?
What is an LLM and how do I use it?
Basics of prompt tuning and prompt engineering
Retrieval Augmented Generation (RAG)
Evaluating generative model performance

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DataBytes: Supporting AI Risk Management in the Analytics Lifecycle
2024-04-30 15:30 - 16:15 | via Zoom
The National Institute of Standards and Technology (NIST) released an AI Risk Management Framework for trustworthy and responsible use of AI and analytics. NIST offers a portfolio of measurements, standards, and legal metrology to provide recommendations that ensure traceability, enable quality assurance, and harmonize documentary standards and regulatory practices. Their framework is very detailed with recommendations across four functions: govern, map, measure, and manage. In this session, we’ll discuss incorporating these recommendations into the analytics lifecycle. Attendees to this session will gain a greater understanding of trustworthy AI best practices as well as user roles and expectations for building responsible analytics.
Join NCDS as Sophia Rowland, a Senior Product Manager focusing on ModelOps and MLOps at SAS, walks us through this important presentation.
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2024 NCDS Spring Career Panel: Analyzing Data Science Careers
2024-03-05 17:00 - 18:00 | via Zoom
2024 NCDS Spring Career Panel Analyzing Data Science Careers – Are you career ready?
You don’t want to miss these data science professionals who provide insight into what it takes to capture the attention of top recruiters in data science and data analytics. Our panelists represent a variety of career stages (a former high school teacher! a Practice Lead and Hollywood script consultant!) and they are ready to discuss what it takes to set yourself apart as you launch your career search.
Join us to learn more about:

What programming languages are in demand now
Unexpected ways to promote your experience
What experiences you should gain early in your career

Moderator: Wing Chan, Senior Vice President, Global Risk Management, Bank of America
Register for the Event
Panelists include:

Paige Spell | Data Scientist at Elder Research: Paige obtained a bachelor’s in Applied Mathematics at Appalachian State University along with minors in Biology, Statistics, and Computer Science. There, she discovered a passion for working with data to make a difference. Paige developed many technical skills but realized she was only scratching the surface. She then went on to earn a master’s degree in Analytics at NC State University, gaining practical experience in model explainability and using machine learning to analyze complex relational claims data. After graduation, Paige worked as a Data Scientist at Red Hat, Inc. forecasting company revenue and product consumption while engaging C-level executives, impacting prompt hiring decisions and influencing business growth. Looking for more diverse problems and a strong technical team, she decided to join Elder Research Inc almost two years ago.
Melinda Thielbar | Vice President of Data Science, Practice Lead at Fidelity Investments: Thielbar is a researcher and statistical software developer with over twenty years of industry experience. Her career ranges from statistics education to developing algorithms for commercial software to Hollywood script consulting. She co-founded Research Triangle Analysts, a 501(c)(3) not-for-profit focused on education and training for people working in the analytics field in the Raleigh-Durham area. Thielbar currently works as a Practice Lead in Fidelity Investments’ Workplace Investing.
Rachini Moosavi | Chief Analytics Officer at UNC Health: Rachini Moosavi, MHA, is the Vice President of Enterprise Analytics at UNC Health. She is passionate about empowering people, delivering value, and improving lives. Over her nearly twenty-year career in healthcare, Rachini has served in analytics, clinical, operational, process improvement, and leadership roles. As a recent graduate of the Carnegie Mellon University CDataO Certificate program, Rachini continues to champion and lead data and analytics enablement within her Enterprise Analytics & Data Sciences team and across The Analytics Community at UNC Health, ensuring that healthcare transformation continues to be catalyzed by insights.
Adam Cottrell | Analytical Consultant at SAS : With more than a decade of experience as a high-performance athletics coach and public educator, Adam is eager to bring his passion for supporting others and a sharp understanding of team dynamics to the data science world. He is driven to understand all types of systems, from the human and societal to the physical and philosophical. This curiosity led him to earning a BS in Physics as well as a Masters in Secondary Science Teaching. As a rowing coach, he instructed athletes of all abilities, aged 12 to 70+, and oversaw the development of many nationally competitive collegiate crews. While coaching, he also worked in the public-school system in several roles across the K-12 spectrum. He hopes to leverage his backgrounds in science, education, and coaching to help bring meaningful insight to a world quickly growing in its need for intelligent, data-driven change.

DataBytes: Becoming A Data Detective - Holding AI Accountable
2024-02-22 12:00 - 13:00 | via Zoom
Bias and brittleness in artificial intelligence (Al) tools are a growing concern. Join Hilke Schellman, Emmy-award winning investigative reporter, Wall Street Journal and Guardian contributor and Journalism Professor at NYU, as she shares key takeaways from her book, The Algorithm: How Al Decides Who Gets Hired, Monitored, Promoted, and Fired and Why We Need to Fight Back Now.
Al is now being used to decide who has access to an education, who gets hired, who gets fired, and who receives a promotion. Algorithms are on the brink of dominating our lives and threaten our human future-if we don’t fight back. During the webinar, Schellmann will share takeaways about the rise of Al in the world of work and show how she tested many of the available tools herself without coding experience.
During our time together, Hilke will share a few key takeaways from the book and answer questions from the audience. You don’t want to miss this.
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DataBytes: Causal AI: The Key to High-Stakes Decision Making
2023-12-05 16:00 - 17:00
The National Consortium for Data Science looks forward to welcoming back Christopher Lam, CEO of Epistamai on December 5th for our next DataBytes event as he discusses Causal AI: The Key to High-Stakes Decision Making.
There has been tremendous attention to the generative AI wave and its enormous potential to transform industries. But there is a hidden wave developing right behind it called causal AI.
Whereas generative AI is optimized for low-stakes decisions like chatbots and image generation, it is not designed to address issues like ethics or trustworthiness that are essential for using AI in high-stakes decisions like credit and hiring decisions. This is where causal AI fits into the picture.
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In this presentation, Christopher Lam will discuss how to use causal AI to build AI systems that society can trust for high-stakes decision making. Lam will show how causal AI can help bridge the gap between symbolic AI and machine learning, demonstrating the value of integrating human knowledge and reasoning about the world to improve how data is analyzed. He will demonstrate through a use case how this more human-centric approach to AI can be used to build fairer and more equitable AI systems that are aligned with society’s democratic values. Finally, he will describe a new causal hierarchy, one that integrates machine learning with causal inference and system dynamics.
There’s a fundamental weakness in how AI systems are being built today, which is due to an overreliance on machine learning and correlation. By strengthening the foundations of AI with causality, we can get a step closer towards developing a grand unified theory of AI. Such a theory is essential for building artificial general intelligence.

About the Speaker – Christopher Lam
Christopher Lam is the founder and CEO of Epistamai, an AI research company based in the Research Triangle that is focused on understanding AI ethics through the lens of causality. The inspiration for his startup came from his work at the Federal Reserve, where he did research on algorithmic bias in credit decisions. He is an evangelist for the emerging field of causal data science, which could help us to solve intractable problems in data science today.

2023 NCDS Fall Career Panel Analyzing Data Science Careers
2023-10-17 17:00 - 18:30
2023 NCDS Fall Career Panel Analyzing Data Science Careers – Are you career ready?
You don’t want to miss these data science professionals who provide insight into what it takes to capture the attention of top recruiters in data science and data analytics. Our panelists represent a variety of career stages and they are ready to discuss what it takes to set yourself apart as you launch your career search.
Join us to learn more about:

What programming languages are in demand now,
Unexpected ways to promote your experience
What experiences you should gain early in your career

Moderator: Dr. Deborah Strohman
Register for the Event
Join the NCDS Talent Pool
Speakers include:

Peter Baquero | Director of AI and Machine Learning at AlixPartners : Peter Baquero is a leader and subject matter expert in the areas of analytics, data management, and data science. He has more than 15 years of experience working both in industry and as a consultant who helps Fortune 100 organizations use their data to realize revenue growth, cost reduction, and risk mitigation. Peter has a record of conceptualizing, promoting, and implementing effective and agile analytic programs. He has transformed data and analytic functions in finance, marketing, risk management, pricing, and corporate strategy for clients in the financial services, retail, and technology sectors.
Suparna Goswami | Senior Research Scientist at RENCI: Suparna Goswami, PhD, is a Senior Research Scientist at RENCI and a co-lead of the Community Data Standards and Knowledge Graph Search Group for the NIH HEAL Data Stewardship Group. Goswami has several years of research experience in the areas of innovation management, user experience research, quantitative research methods; and in leading interdisciplinary, multi-institutional research projects. In addition to her academic background, Goswami has years of industry experience in the development and implementation of large scale multi-organizational information technology systems. She has published in premium journals and conferences in the areas of information systems management and computer human interaction.
Reiko Nakashima | Director of Computational Biology in Machine Learning and Computational Sciences at Pfizer: Reiko is Director of Computational Biology in Machine Learning and Computational Sciences (MLCS) group at Pfizer. With her computational, biostatistical, and epidemiological skills, she leads computational method development to analyze various types of large biological data including high-throughput sequencing data. Before joining Pfizer, she was Assistant Professor at Brigham and Women’s Hospital and Harvard Medical School where she led cancer genomics, cancer immunology, and biomarker discovery studies using whole-exome sequencing, RNA-sequencing, clinical and pre-clinical studies, and longitudinal population-based cohorts.
Estevan E. Torres Jr | Senior Financial Analyst at Bank of America : Estevan E. Torres Jr. is a Systems Engineering graduate from the University of North Carolina at Charlotte with a diverse background spanning multiple industries, including manufacturing, supply chain controls, and finance. Estevan has been an integral part of Bank of America for the past four years. Throughout his journey at the bank, he has gained valuable experiences in various departments, from Global Procurement, Global Risk, and now finding himself in Staff Support Finance. He has a personal connection to assisting the Latinx, LGBTQ+, and other underrepresented communities. Estevan volunteers his time giving back to combat stigmas in the mental health and low-income population locally in his hometown of Charlotte, NC. He is passionate about promoting mental wellness and supporting individuals in their own career progression.

DataBytes: The Risks of Facial Recognition Technology: Dismantling the First Amendment Defense
2023-10-11 15:30 - 16:30
In a lawsuit challenging its surveillance activities, Clearview AI used the First Amendment as a defense. The facial recognition technology company argued that the creation and use of its surveillance product was First Amendment protected speech. Join Talya Whyte, third-year law student at New York University, as she presents a case study on the parties’ basic arguments, Clearview AI’s characterization of its activities as “speech,” and the implications of this argument. Attendees will understand how facial recognition technology works and the risks and harms inherent in its building and implementation, and gain the knowledge to make more informed legal, policy, and technical choices about the implementation of AI-based surveillance technology.
Talya Whyte is a third year law student at New York University. Her research interests lie at the intersection of new technology, society, public trust, and digital rights. She is a 2023 Google Legal Scholar, a Student Fellow at the Engelberg Center on Innovation Law & Policy, and NYU Cyber Scholar. Whyte hopes for a thoughtful and humanitarian integration of technology into existing legal and societal frameworks.
Register for the Event

Scaling Up: Exploring Articulation Agreements Between Two-Year and Four-Year Institutions: Wake Tech and Shaw University
2023-10-05 15:00 - 16:00
Articulation agreements between two year and four year institutions aren’t crafted overnight. Join this conversation between leaders at Shaw University and Wake Tech as they walk our audience through the essential components of an articulation agreement between a two year institution and a four year institution. Topics that they will address include but are not limited to the following: Community college bridge programs, pitfalls to avoid, and mapping certifications into the agreement.
Speakers:
James Brown, Shaw University – Department Head of Computer Science at Shaw University
Kathy Frederick, Wake Tech – Director of Student Work Experience Employer/University/Advisory Partnerships
Register Here

DataBytes: AI in Target Identification and Drug Discovery: Transforming the Future of Medicine
2023-08-22 12:00 - 13:00 | via Zoom
The National Consortium for Data Science looks forward to hosting Kimberly Robasky, Associate Director of Machine Learning/AI at Arrakis Therapeutics, on August 22 for our next DataBytes event as she discusses AI in Target Identification and Drug Discovery: Transforming the Future of Medicine.
Register Here
Artificial intelligence (AI) is taking a transformative role in target identification and drug discovery. Today, AI algorithms can analyze vast, multi-modal datasets to identify drug targets, accelerate lead compound discovery, and optimize drug design. AI is being used by biotechnology companies around the world to compress timelines and improving clinical trial outcomes. Join us to uncover the data-driven revolution in personalized medicine enabled by AI-driven drug development.

Data Matters 2023
2023-08-07 - 2023-08-11 | via Zoom
Data Matters™ is a week-long series of one and two-day courses aimed at students and professionals in business, research, and government. The short course series is sponsored by the Odum Institute for Research in Social Science at UNC-Chapel Hill, the National Consortium for Data Science, and RENCI.
Registration is now open for the traditional Data Matters series which will be held August 7 – 11, 2023. Register here.
Data Matters gives students the chance to learn about a wide range of topics in data science, analytics, visualization, curation, and more from expert instructors. Registration is now open; reserve your spot now!

DataBytes: AI Ethics Through the Lens of Causality: A Theory of Fairness
2023-06-20 16:00 - 17:00
The National Consortium for Data Science looks forward to hosting Christopher Lam, CEO of Epistamai on June 20 for our next DataBytes event as he discusses AI Ethics Through the Lens of Causality: A Theory of Fairness.
View a recording of the event here.
To understand fairness, one must unify central ideas from the social sciences and humanities to mathematics and computer science. Join Christopher Lam, CEO of Epistamai, as he shows how to model a principal cause of algorithmic bias and directly map it to the two fundamental laws of causal inference. Additionally, he will show how to bridge the field of causal inference to machine learning, providing us with a novel way to visualize the different ways that a supervised machine learning model can discriminate. These causal models may help policymakers on both sides of the aisle to modernize AI regulations so that they are aligned to society’s values.
