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In this issue:
Election + Voting Data Resources
Latest HDSR Podcast Episode
Featured Event
Upcoming Events
Recommended Reads
Student Program Opportunities
Postdoctoral Fellowship Opportunity
Full-Time + Internship Opportunities
October 27, 2022
Two T-Rexes make their way across the Harvard Yard | Rose Lincoln, Harvard Staff Photographer
Dear Friends, 

Congratulations to John Quackenbush, HDSI Steering Committee Member, on being elected to the National Academy of Medicine (NAM)!

With the U.S. midterms approaching, we are exploring election and voting data this week with the collection of resources below. In addition, the latest Harvard Data Science Review Podcast episode features four experts who discuss their predictions for the upcoming midterm elections and how these elections might impact the presidential race in 2024.

We are looking forward to seeing you at the HDSI Annual Conference 2022! Reserve your tickets now for the Day 2 Plenary Sessions and view the updated list of confirmed speakers.

Looking for a work in data science? The Dominici Lab, led by HDSI Faculty Co-Director Francesca Dominici, is seeking a Senior Programmer to join its dynamic team. Check out more full-time opportunities at Harvard and internship opportunities at Microsoft Research New England and Netflix below!

Happy (almost) Halloween! Have a safe and fun Halloweekend!

All the best,

The Harvard Data Science Initiative
Election + Voting Data Resources
Midterm Voting Intentions Are Divided, Economic Gloom Persists
Pew Research Center

Voting and Registration Visualizations
United States Census Bureau

MIT Election Data + Science Lab
Key facts about Black eligible voters in 2022
Pew Research Center

Key facts about Hispanic eligible voters in 2022
Pew Research Center

Key facts about Asian American eligible voters in 2022
Pew Research Center
Do You Live in a Political Bubble?
The New York Times

Enter your address to see the political party of the thousand voters closest to you.
POLITICO 2022 Election Forecast: Ratings, Predictions & Key Races

POLITICO analyzed every House, Senate and gubernatorial seat to determine who it thinks will win the 2022 midterm elections. 
FiveThirtyEight 2022 Midterm Election Forecast

Want to see how the odds would change if Republicans or Democrats win specific races?
Check out the interactive version of our forecast.
See Everything the White House Wanted, and Everything It Got
The New York Times

With the midterms less than three weeks away, The Upshot examined the president’s policy goals and Congress’s successes in previously unreported detail. It matched every single line of spending and revenue in the jobs and families plans from Mr. Biden’s 2022 budget with cost estimates for the five large policy bills passed by Congress in the last year.
Latest HDSR Podcast Episode
It's Election Time Again – Do We Predict Better This Time?
Harvard Data Science Review Podcast | Episode 22
With the 2022 U.S. midterms right around the corner, this month’s podcast is all about elections. Who is going to win and why? Listen to four experts discuss their predictions for the upcoming midterm elections in November and how these elections might impact the presidential race in 2024. 

Episode Guests:
Featured Event
Tuesday, November 15
9:00 AM – 5:00 PM EST

Science + Engineering Complex, Harvard SEAS
Wednesday, November 16, 2022
8:00 AM – 6:30 PM EST

Klarman Hall,
Harvard Business School
Two days of in-person workshops, tutorials, + plenary sessions
The invites you to the HDSI Annual Conference 2022, a two-day, in-person event that will showcase data science in research and education through panels, keynotes, workshops, and tutorials featuring speakers from across Harvard, academia, and industry. Join us to connect with data science professionals, expert methodologists, and educators across disciplines to ignite new discoveries with impacts on health, education, economics, social policy, business, and the humanities.

This event is free and open to the public. Ticket required for admission. Please RSVP to reserve your spot.
Tickets for the Day 1 tutorial and workshop are sold out, but there are still tickets available for the Day 2 plenary sessions!

Day 2 Plenary Sessions:
  • Academic Keynote
  • Industry Keynote
  • Lightning Talks: HDSI Postdoctoral Fellows
  • Panel 1: Communicating Data Science – Trust with complexity
  • Panel 2: Social Impact Computing – Building an emerging field
  • Panel 3: Agent-Based Modeling – Complex ecosystems in silico
  • Panel 4: Data Science + Climate – Connecting planetary + human health
Read about some of our confirmed speakers:
Natalie Dean (Assistant Professor, Biostatistics and Bioinformatics, Emory Rollins School of Public Health)

Panel 1: Communicating Data Science – Trust with complexity

Natalie completed her Master’s degree and PhD in biostatistics at Harvard University. 
Lace Padilla (Assistant Professor, Cognitive and Information Sciences, University of California Merced)

Panel 1: Communicating Data Science – Trust with complexity

Lace's interests lie at the intersection of Information Visualization, Behavioral Decision Making, and Data Science.
Milind Tambe (Gordon McKay Professor of Computer Science, Harvard SEAS)

Panel 2: Social Impact Computing – Building an emerging field

Milind is also Principal Scientist and Director of "AI for Social Good" at Google Research. 
Yang Zhang (Director of the Model Development, Bank of Canada)

Panel 3: Agent-Based Modeling – Complex ecosystems in silico

Yang leads high-quality research that supports the renewal of the Bank’s monetary policy framework.
Upcoming Events
Ambiguous Dynamic Treatment Regimes: A Reinforcement Learning Approach
Hosted by MIT Operations Research Center (ORC)
Thursday, October 27, 2022
4:15 PM EST
77 Massachusetts Avenue
Building E40-103, Room E51-145
  • Soroush Saghafian, Associate Professor, Harvard University; HDSI Faculty Affiliate
Join in-person. No registration necessary!
Using RStan for Bayesian Statistics
Thursday, October 27, 2022
5:00 PM – 6:00 PM EST
Virtual (Zoom)
Hosted by R User Group at the Harvard Data Science Initiative
  • Fayette Klaassen, Postdoctoral Researcher, Department of Global Health and Population, Harvard T.H. Chan School of Public Health
Join RUG at the HDSI to learn about how you can use RStan to perform Bayesian statistics in R! This talk will provide an introduction to what Bayesian statistics and RStan are and how you can get started using them.

Fayette Klaassen works on Bayesian statistical models to predict COVID-19 infections. Fayette will introduce how to write a Stan program and describe the workflow using Stan as well as go over some example Stan models.
Optimal nonparametric estimation of heterogeneous
causal effects 
Thursday, November 3, 2022
3:30 PM – 5:30 PM EST
Hawes Hall, Classroom 203, Harvard Business School
HDSI Causal Seminar: Edward Kennedy, Carnegie Mellon
Edward Kennedy, Associate Professor of Statistics and Data Science, Carnegie Mellon University

Edward's research interests include causal inference, missing data, functional estimation, machine learning, and general nonparametrics, especially in settings involving high dimensional and otherwise complex data.

Estimation of heterogeneous causal effects -- i.e., how effects of policies and treatments vary across units -- is fundamental to medical, social, and other sciences, and plays a crucial role in optimal treatment allocation, generalizability, subgroup effects, and more. Many methods for estimating conditional average treatment effects (CATEs) have been proposed in recent years, but there have remained important theoretical gaps in understanding if and when such methods make optimally efficient use of the data at hand. This is especially true when the CATE has nontrivial structure (e.g., smoothness or sparsity). Read more.
Symposium on Science, Technology, + the Human Future
November 3 – 5, 2022
Harvard University
Hosted by the Program on Science, Technology + Society at Harvard University in celebration of its 20th Anniversary
The Program on Science, Technology & Society is celebrating its 20th anniversary with a Symposium on Science, Technology and the Human Future, to be held at Harvard from November 3-5, 2022. This major event will feature a wide range of high profile speakers across political, academic, and broader society. 
The Symposium begins at 5pm on Thursday, November 3 with a keynote lecture by novelist Arundhati Roy, including performances of original music and fiction written by Harvard students. We continue on Friday with panels on the role of science and technology in shaping the human future, including the future of knowledge, life, policy, and cities. Saturday includes open discussions on how STS can position us to better understand and govern ourselves, our societies, and our Earth.
Biomedical Informatics Entrepreneurs Salon: Anne Wojcicki, 23andMe
Tuesday, November 8, 2022
5:00 PM – 6:00 PM EST
Virtual (Zoom)
Hosted by the Harvard Office of Technology Development and the Harvard Medical School Department of Biomedical Informatics
  • Anne Wojcicki, CEO and Co-Founder of 23andMe

Anne is a pioneer in the direct-to-consumer DNA testing space and her vision and persistence have allowed 23andMe to provide people with unprecedented access to genetic information. Through its research platform, 23andMe has brought personalized medicine directly to millions of consumers. Read more.

Data and Economic Principles in Video Games
Thursday, November 10, 2022
1:30 PM – 2:30 PM EST
Virtual (Zoom)
HDSI Industry Seminar: Tammy Levy,
Tammy Levy, Chief Games Officer,

At, a startup pioneering streamer-led multiplayer community games, Tammy draws on her background in computer science and design to drive the decisions behind the business and the fun of building games.

Underneath the fun of games we can find complex economies. In the last 15 years, with the rise of accessible broadband internet, video game developers have been able to regularly release game updates or "patches" through a process called live servicing. In addition to new content, game designers often add, remove, and rebalance the resources in the game– effectively manipulating the game's economy on a regular basis. In this talk, I will cover the basic principles of game economies and the core business KPIs used to monitor a game's performance. Then I'll walk through real examples behind the data-driven decisions for game optimization.
Recommended Reads
Prioritizing municipal lead mitigation projects as a relaxed knapsack optimization: a method and case study
Wiley Online Library

A simple process for estimating child health impact at a parcel level by cleaning and synthesizing municipal datasets that are commonly available but seldom joined due to data quality issues authored by IACS Fellow Isaac Slavitt.

How AI Can Help Diagnose Rare Diseases
Harvard Medical School

New model acts as search engine for large databases of pathology images, has potential to identify rare diseases and therapies. Senior author HDSI Faculty Affiliate Faisal Mahmood.
The United States’ Unamendable Constitution
The New Yorker

An interactive piece of work funded in part by the Inequality in America Initiative and the HDSI on how our inability to change America’s most important document is deforming our politics and government by Jill Lepore, David Woods Kemper ’41 Professor of American History at Harvard University. 

Labs Enable Large-Scale Research
Harvard Business School

Collaborations leverage Harvard’s strengths and resources, featuring HDSI Faculty Affiliate Scott Duke Kominers and HDSI Annual Conference 2022 speaker Hima Lakkaraju.
Student Program Opportunities
Introduction to Data Science with Python
Free, self-paced course
8 weeks, 3 – 4 hours per week
Learn the concepts and techniques that make up the foundation of data science and machine learning
About the course:

Every single minute, computers across the world collect millions of gigabytes of data. What can you do to make sense of this mountain of data? How do data scientists use this data for the applications that power our modern world?

What you'll learn:
  • Gain hands-on experience and practice using Python to solve real data science challenges
  • Practice Python programming and coding for modeling, statistics, and storytelling
  • Utilize popular libraries such as Pandas, numPy, matplotlib, and SKLearn
  • Run basic machine learning models using Python, evaluate how those models are performing, and apply those models to real-world problems
  • Build a foundation for the use of Python in machine learning and artificial intelligence, preparing you for future Python study
D^3 Learning Sprints: Everyday Analytics
Meets weekly on Wednesdays
12:15 – 1:45 PM EST
November 9 – December 7 (no class on November 23)
A month-long program designed to help students understand and process data as it is typically communicated via news media and popular culture
  • Emily Oster, Professor of Economics, Brown University
Everyday Analytics will focus on four key analytic concepts which, when deeply understood, can feed back into better understanding of data in and outside the workplace. The goal of the program is to enhance facility with these concepts to develop fluency in applying them in a wide range of situations. Front Row students will have an opportunity to work directly with data, alongside analysis of existing evidence.
Postdoctoral Fellowship Opportunity
Harvard Data Science Initiative Postdoctoral Fellowship Program 
Deadline: Monday, November 14th, 11:59 PM EST
The Harvard University Data Science Initiative is seeking applications for its Harvard Data Science Initiative Postdoctoral Fellows Program for the 2023-2024 academic year. The normal duration of the Fellowship is two years. Fellows will receive a generous salary as well as an annual allocation for research and travel expenses. 

We are looking for researchers whose interests are in data science, broadly construed, and including researchers with a primarily methodological focus as well as researchers who advance both methodology and application. Fellows will be provided with the opportunity to pursue their research agenda in an intellectually vibrant environment with ample mentorship. We are looking for independent researchers who will seek out collaborations with other fellows and with faculty across all schools of Harvard University.

We recognize that strength comes through diversity and actively seek and welcome people with diverse backgrounds, experiences, and identities.
Full-time + Internship Opportunities
Recently Posted Jobs at Harvard
Data Science Project Management Specialist
Harvard Faculty of Arts and Sciences

Pre-doc Fellow
Harvard Business School

Connected Systems Software Developer
Harvard John A. Paulson School of Engineering and Applied Sciences

Data Engineer
Harvard Medical School

Principal Data Engineer
Harvard Medical School

Assistant Director, Sustainability Data Analytics
Harvard University Office for Sustainability

Senior Research Computing Systems Software Engineer
Harvard Faculty of Arts and Sciences

Bioinformatics Scientist
Harvard Faculty of Arts and Sciences

Bioinformatician II
Harvard T.H. Chan School of Public Health
Senior Programmer
Harvard T.H. Chan School of Public Health

Statistical Analyst/Programmer
Harvard T.H. Chan School of Public Health

Senior Data Scientist
Digital, Data, and Design (D^3) Institute, Harvard Business School

Data Scientist, D^3 Institute
Digital, Data, and Design (D^3) Institute at Harvard Business School

Bioinformaticist I
Harvard Faculty of Arts and Sciences

Senior Full Stack Software Engineer
Harvard Faculty of Arts and Sciences

Data Science Specialist
Institute for Quantitative Social Science (IQSS)

Applied Research Statistician
Harvard Law School

SAS Programmer I
Harvard T.H. Chan School of Public Health
Internship Opportunities
Research Intern Machine Learning for Biology and Healthcare
Microsoft Research New England

Research Intern – Economics and Computation
Microsoft Research New England
Research Intern – Artificial Intelligence
Microsoft Research New England

Experimentation and Causal Inference Intern, Data Science and Engineering
Engage + Connect
Interested in reading more about data science projects and news at Harvard? Check out our blog for features, top stories, and what we are learning now in the world of data.
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