ASA Early Career Profiles: Bachelor’s-Level Graduates in Statistics and Data Science

Organized by the ASA Section on Statistical Education

    What can I do with an undergraduate degree in statistics or data science? Take a look at what these individuals are doing. They are employed at early stages of a career after graduating from a bachelor’s degree program that included training in statistics or data science.

      Travis Britain

      Biography

      Undergraduate School: Duke University
      Graduation Year: 2015
      Position: Associate Consultant – Corporate Strategy
      Company: Liberty Mutual Group
      Sector: Consulting

      Background
      • BS in statistical science and economics
      • Bayes Impact Fellowship for nonprofit data science
      • Active in nonprofit and foundation impact evaluation
      Job Description
      • Provide internal strategy consulting services for Liberty Mutual Insurance Group, a Fortune 100 company, focused on high-impact problems in strategic planning; financial, competitive, and operational analysis; and capital investment
      • Sample projects include strategy design for Liberty Mutual Foundation, catastrophe claims operating model review, and Ireland profitability analysis and turnaround strategy
      Statistics and Data Science at Work

      My industry (insurance) is all about understanding risk. I may not be writing R script every day in my strategy job, but the mindset I developed from studying statistics is absolutely priceless. Strategy consulting—particularly in my industry—demands an acute appreciation of uncertainty, an ability to find elegance in complex systems, and—perhaps most importantly—the ability to synthesize a large volume of complex information and communicate the findings to a diverse (often nontechnical) audience in a way they can understand and act upon.

      Favorite Undergraduate Statistics Class

      My favorite undergraduate statistics class was, bar none, Statistics of Causal Studies, in which we learned the theory of and various practices for inferring causation from not only formal experimental studies (such as an RCT), but also observational studies using techniques such as propensity score matching. At the time, I was helping a nonprofit in Boston better understand how to understand their social impact, so I had a really unique opportunity to apply what I was learning in the classroom.

      Advice for Students

      It hurts my brain to think about how rapidly the world of data and information is evolving. By studying statistics, you’re already well ahead of the pack! The best advice I can give to you now is to seek out opportunities to apply statistical methods to a wide variety of disciplines to best position yourself for the future. In undergrad, I used statistics for applications in health care, traffic safety, public policy, finance and economics, law, engineering, and countless others. Each discipline provides new learnings and new techniques that reinforce the others, and by building a breadth of experiences as an undergraduate, you’ll be in a better place to reflect on what areas you enjoy the most and where you can add the most value to the world.


      Jieyu Gao

      Biography

      Undergraduate School: Purdue University
      Graduation Year: 2016
      Position: Emerging IT Leaders
      Company: Purdue University
      Sector: Science/Technology

      Background
      • Undergraduate researcher in Alex Chubykins lab
      • Data analysis using Jupyter Notebook and R
      Job Description
      • Research computing TACC STATS project
      • Analyze the data to show the visualization of the performance of clusters
      • Python, Jupyter Notebook, Linux
      • Faculty project
      • Providing suggestions on data analysis of different fields of research projects
      Statistics and Data Science at Work

      Data visualization tools, including bar graph, histogram, and error bar graphs; scientist test: ANOVA, F-test, independent t test

      Favorite Undergraduate Statistics Class

      Experimental Design was a very practical and useful class, especially introducing how to design experiments to gather the most useful data at the designing stage.


      Brittany Cohen

      Biography

      Undergraduate School: Duke University
      Graduation Year: 2014
      Position: Quality Assurance Engineer
      Company: Applied Predictive Technologies
      Sector: Science/Technology

      Background
      • BS in statistics, minor in computer science, graduated cum laude
      • Internships with Publishers Clearing House, Bureau of Economic Analysis, and Applied Predictive Technologies (turned into full-time opportunity)
      Job Description
      • Validate front-end software and back-end analytics
      • Derive new analytics to be implemented in our software platform
      • Work with product managers and client users to understand business use cases
      Statistics and Data Science at Work

      At APT, we develop a software platform that allows major companies to make data-driven decisions. We are constantly looking for new analytic methodologies to implement and for ways to improve our existing methodologies. I have been able to get involved with the team that uses statistics to develop new significance formulas for our complex analyses. I have been able to apply learnings from my probability course, among others, to take the variance of unintuitive expressions.

      Favorite Undergraduate Statistics Class

      My favorite undergraduate course was Statistical Consulting, which is a course I took as an elective. In this course, we helped researchers and organizations on campus that were in the middle of doing research and had statistical questions. This course was really exciting to me because it allowed me to understand the importance of statistics in a variety of fields. It was exciting to see that, even in the middle of my college education, I was able to make an impact in research in multiple industries.

      Advice for Students

      I think one of the most advantageous things I did during my college career was to combine statistics with computer science. The two go hand-in-hand, and I was fortunate enough to find a job that allows me to continue using my statistics knowledge!


      Ariana Montes

      Biography

      Undergraduate School: California Polytechnic University, San Luis Obispo
      Graduation Year: 2014
      Position: Configuration Engineer
      Company: Apttus
      Sector: Science/Technology

      Background
      • BS in statistics
      • Summer research 
intern at Cal Poly
      Job Description
      • Responsible for the design and implementation of CPQ for a reputable Fortune 500 company
      • Advanced knowledge of product and pricing architecture
      • Involved in identifying and delivering complex requirements
      • Work closely with project team to deliver an advanced design
      • Develop excellent working relationships with clients
      Statistics and Data Science at Work

      My current role is not heavy in statistics, but I have been able to utilize a lot of knowledge from my undergraduate education related to consulting. I am on the phone with clients gathering requirements and come up with practical solutions to solve their business needs.

      Favorite Undergraduate Statistics Class

      Statistical Consulting and Analysis of Cross-Classified Data

      Advice for Students

      Network as much as you possibly can! Try to attend conferences in the industry you’re interested in, introduce yourself to as many people as possible, and connect with everyone on LinkedIn. You’ll be surprised how important networking is in your future career.


      Emily Hadley

      Biography

      Undergraduate School: Duke University
      Graduation Year: 2015
      Position: College Adviser
      Company: College Advising Corps
      Sector: Government/Education

      Background
      • BS in statistical sciences and BA in public policy studies from Duke University
      • Internships with the New Hampshire Governor’s Office of Citizen Services and The Education Trust, both giving me the opportunity to apply my statistics skills in the policy realm
      • Statistics senior project and public policy senior thesis that focused on predicting and addressing high-school dropout in rural North Carolina
      Job Description
      • AmeriCorps position looking to increase college access for students from all backgrounds by placing recent college graduates in high-need schools
      • Advise 120 seniors at a low-income, rural high school in North Carolina on post-secondary opportunities
      • Organize college access events, including financial aid sessions and college representative visits for all 540 students
      • Track data to measure impact of programming
      Statistics and Data Science at Work

      Though my job title may not indicate a data focus, data is a crucial part of my work. On the job, I am always collecting data about the students I work with, from demographic information to standardized test scores to counting one-on-one interactions with individual students. I use this data to understand my strengths and weaknesses and set goals. For example, my data show that female students are far more likely to seek out my help repeatedly while male students are likely to come once, so I have developed programming to re-engage my male students. The national office uses adviser data to tell a larger story of the importance of College Advising Corps. I also serve as a College Adviser Corps data and policy fellow, where I am on a team of researchers investigating how College Advising Corps can use both quantitative and qualitative data to inform its work, particularly as it relates to underclassmen.

      The community I serve also has a dearth of statisticians, so I have been called upon to do pro bono data analysis for the school board, the local community college, and other institutions. This has included working in development of data tracking systems and survey methods, as well as analysis of existing data sets such as regression and model building.

      Favorite Undergraduate Statistics Class

      Statistical Decision Analysis, as it applied Bayesian theory to logical decision making, and Statistical Consulting, as it helped develop both analysis and communication skills as they related to statistical analysis of community projects

      Advice for Students

      I believe one of the greatest powers of data and statistics is to shine a spotlight on issues that are often neglected, particularly in the policy world. So my advice is to not be afraid of following a path that is not traditional in the realm of statistics. Once a community knows you are a statistician, they will often seek you out for a wide variety of projects and your statistical expertise will grow in surprising, relevant ways.


      Trevor Smith

      Biography

      Undergraduate School: Amherst College
      Graduation Year: 2016
      Position: Analyst
      Company: Hillary for America
      Sector: Government/Education

      Background
      • Statistics and political science majors
      • Internship with 
Capital One
      • Competed at UMASS DataFest
      Job Description
      • Analysis of digital ad campaigns
      • Constructing and publishing performance reports
      • Running tests
      Statistics and Data Science at Work

      I use stats on a daily basis for my job. I use R to run analyses on different ad campaigns. I also use my statistical background to help identify potential sources of bias in various experiments that we create and run.

      Favorite Undergraduate Statistics Class

      Advanced Data Analysis—I liked the broad coding experience and the ways that we connected coding to theoretical statistics and real-world examples.

      Advice for Students

      It is really important to get a solid understanding of the theory behind statistics while studying it. Most of the coding can be learned quickly on the job.


      Corinne Idzorek

      Biography

      Undergraduate School: 
St. Olaf College
      Graduation Year: 2015
      Position: Business Intelligence Analyst
      Company: 
Thrivent Financial
      Sector: Financial/Banking

      Background
      • Economics and mathematics double-major, with a concentration in statistics
      • Summer internship as a marketing analytics intern at Thrivent Financial
      • Courses in statistical modeling, advanced statistical modeling, probability theory, statistical theory, algorithms for decision making, and econometrics
      Job Description
      • Create predictive models from customer data that determine which products are marketed to whom
      • Explore Big Data opportunities to bring in new, publicly available data for prospecting
      • Gather and manipulate internal data based on requests to help evaluate current business and influence change
      Statistics and Data Science at Work

      In my position, we use statistics every day. We are constantly evaluating and cleaning data, utilizing multiple exploratory data analysis techniques to find important variables, and building predictive models. We test everything from logistic regression models to neural networks and ensemble models for every project. Ultimately, we have to be able to communicate our methods, decisions, and results to others within the organization.

      Favorite Undergraduate Statistics Class

      Statistical Modeling and Advanced Statistical Modeling were my favorite classes because we learned so many useful techniques for cleaning, exploring, analyzing, and modeling real data that I use every day at work. We also learned how to communicate techniques and results so they were accessible to everyone, which was so important to learn from the start.

      Advice for Students

      Every department at pretty much every company wants someone who can take their data and find meaning in it. Regardless of what sector or area 
of business you’re interested in, there are 
opportunities. With Big Data becoming the norm, everyone wants to get their hands on more information and be able to get something (statistically) significant from it.


      Jonathan Jordan

      Biography

      Undergraduate School: Amherst College
      Graduation Year: 2015
      Position: Investment Banking Summer Analyst
      Company: 
Nymex Capital
      Sector: Financial/Banking

      Background
      • BA in economics and statistics
      • Statistics fellow
      • Investment banking 
summer analyst
      Job Description
      • Build operating models with DCF, M&A comps, and public comps
      • Conduct research on industry, competitors, expected synergies, and historical prices
      • Prepare pitch books that include industry overview, model, and analysis
      Statistics and Data Science at Work

      At Nymex, I mostly use data to understand the stories of particular industries and high-level trends. Organizing and understanding data regarding growth rates, prices, and volume are the most common ways I use my statistics background.

      Favorite Undergraduate Statistics Class

      Intermediate Statistics—great introduction to regression and my first real experience diving into a data set to tell an interesting story

      Advice for Students

      Take a statistics class as early as you can!


      Dana Udwin

      Biography

      Undergraduate School: Smith College
      Graduation Year: 2014
      Position: Data Analytics Consultant
      Company: Massachusetts Mutual Life Insurance Company
      Sector: Insurance/Actuarial

      Background
      • Mathematics major with a concentration in statistics
      • East Asian languages and literature minor
      • Summer undergraduate research fellow at the National Institute of Standards and Technology (2013) researching contributing factors to performance of face recognition technology on video
      • Developing statistical activities in R for the classroom with Nicholas Horton (Amherst College)
      • Ben Baumer’s (Smith College) undergraduate data science course
      • Mathematical statistics in the UMass graduate-level statistics catalogue and machine learning in the UMass graduate-level computer science catalogue
      • Supporting the Smith College Mathematics and Statistics Department as a teaching assistant and grader for students of introductory statistics (and related classes)
      Job Description
      • Analyze both internally and externally sourced data using Python, R, and other computational implements of statistical inquiry to create tactical and strategic value for MassMutual
      • Visualize complex data using a suite of web programming tools (e.g., HTML, Twitter Bootstrap, JavaScript, and associated libraries for data manipulation such as Crossfilter and dc.js)
      • Attend graduate-level data science courses in the statistics and computer science departments at the University of Massachusetts, Amherst to supplement project-based learning
      Statistics and Data Science at Work

      We are constantly using statistics both to serve MassMutual’s broader mission of selling policies and to streamline or improve internal processes. For example, one project utilized k-means clustering to identify subpopulations within the MassMutual consumer base. Even when building dashboards to visualize large, messy data, we are thoughtful and methodical in choosing what metrics are valuable and how to calculate and portray these metrics in a clear, accurate way. We built such a visualization to track enterprise-wide spend, an example of supporting internal processes.

      Favorite Undergraduate Statistics Class

      Ben Baumer’s undergraduate data science course at Smith College was a great crash course in all things data science: databases, large-scale analyses, and exploiting outside sources to discover knowledge with efficacy and panache (look up Mark Hansen to see Big Data and art collide).

      Advice for Students

      Take the coursework that interests you. Become a tutor to help you review, refresh, and test your own understanding. A couple of programming classes will come in handy later on. Look for research opportunities in any department at your school or domain out in the workforce; there are interesting problems in unexpected places that can be solved with data. And statistics is awesome! We need statistical prowess (YOU) to make valuable the massive and expanding wealth of data in our world.

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