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

1 August 2017 766 views No Comment

Organized by the ASA Section on Statistical Education

What can you do with an undergraduate degree in statistics or data science? Take a look at what these individuals are doing. They are employed at the early stages of their careers after graduating from a bachelor’s degree program that included training in statistics or data science. Check out other profiles.

Kurt Bembridge

Undergraduate School: Howard University
Graduation Year: 2006
Position: Para-Professional
Company: District of Columbia Public Schools
Sector: Government/Education

Background

MS in data analytics in progress

Job Description
  • Assist teachers with daily classroom needs such as completing attendance, communicating with parents, and maintaining a positive and clean classroom environment.
  • Lead small-group and individualized educational activities with students.
  • Provide support with behavior management.
  • Engage students throughout various times of the day with multiple ways to access information and learning.
Statistics and Data Science at Work

I do not analyze data in my job, but data science is used to track children’s progress and monitor students.

Favorite Undergraduate Statistics Class

Econometrics and Numerical Analysis

Advice for Students

Learn how to use software in your classes. Although software isn’t a main focus of most undergraduate students, please learn SAS, R, Java, Python, or any language.

Sergio E. Betancourt 

Undergraduate School: University of Toronto
Graduation Year: 2015
Position: Senior Technology Analyst
Company: Citigroup
Sector: Financial/Banking

Background 
  • HBSc with Distinction from the University of Toronto, St. George—Specialization in statistical sciences, major in mathematics, and minor in economics
  • Interests and extracurriculars include being a data strategist with Toronto’s Hispanotech Professional Association (March 2017 – Present), a dance performer with Steps Dance Studio’s Performance Team (January 2016 – Present), and a steering committee member of Citilife Canada (November 2015 – Present)
  • Twelve-month internship at Ericsson Canada as a pricing and bid and proposal coordinator (August 2013 – August 2014)
  • Extracurricular involvement while in school: President of the Statistical Sciences Association of Students (September 2014 – May 2015), co-president of the Economics
  • Students’ Association (September 2012 – May 2014)
Job Description

I have been a technical applications and business analyst for different technology groups at Citigroup, currently Equities Electronic Execution. Before this, I worked with Global Data Services and Prime Finance. My team and I provide the tools and capabilities to access markets, execute efficiently, and trade algorithmically and electronically. The technologies I use the most are MongoDB, Python, UNIX, Perl, R, Elasticsearch, VBA, SQL, ITRS Geneos, and Cloud.

Statistics and Data Science at Work 

The focus of my role is on data availability, integrity, and fast transmission. Although this does not require an extensive knowledge of statistical practices, it relies on technology and algorithms to enable movement and preserve integrity. My background in statistics and mathematics has proven incredibly useful in picking up technologies and programming quite quickly—I script with ease and deal with complex systems daily.

Favorite Undergraduate Statistics Class

STA490–Statistical Consultation, Communication, and Collaboration: This class provided valuable exposure to the role of a statistician in experiment design and analysis. We collaborated with investigators from other departments to perform both elementary and sophisticated analysis. This meant access to a real-world data set, as well as a number of issues that come up in empirical research.

Moreover, the communication techniques we learned, and the opportunity to employ them through numerous presentations, improved our ability to digest complex issues quickly and communicate knowledge using different levels of complexity.

STA414–Statistical Methods for Machine Learning and Data Mining: Valuable course on the mathematical and statistical foundations of data mining and pattern recognition. Not only was this course incredibly challenging and stimulating, but also useful in understanding how to practice statistics in the modern world. We undertook several eye-opening projects that shed light on the foundations of some of the modern world’s greatest advancements.

Advice for Students
  • Do not neglect your extracurricular activities, and pick up as much computer science while you are still in school.
  • Try to get as much professional and research experience while in university to motivate your journey into the statistical sciences.
  • Take up classes and projects outside of the quantitative sciences to increase your creativity (vital in all aspects of life) and adaptability.

Elizabeth Miller

Undergraduate School: Florida State University
Graduation Year: 2014
Position: Senior Analyst
Company: Momentum Consulting Corp.
Sector: Consulting

Background

I graduated with three degrees: Statistics (BS), Actuarial Science (BS), and Applied Mathematics (BS). I also interned with an agriculture biotechnology company in the R&D department, serving as a data scientist, in Research Triangle Park, North Carolina.

Job Description
  • Versatile business intelligence professional who uses her strong communication skills and hands-on experience working with various data analysis projects to provide effective results for clients
  • Proficient in requirements gathering, data analysis, data quality assessment, machine learning, database management, and statistical analysis
  • Bilingual (English/Spanish) and comfortable working with people at all levels of a business, from technical teams to key stakeholders
Statistics and Data Science at Work

Depending on the nature of the project, I use statistics building models that serve as the business solution. I also provide education to the client regarding statistical analysis in an applied manner.

Favorite Undergraduate Statistics Class

Time Series was my favorite course, partially due to how engaging the professor was, but also to how much application I could see with it besides gaining theoretical knowledge.

Advice for Students

Ask questions always. Do not limit yourself when applying for internships or jobs, even though you may not have job experience or the desired education level. It takes hard work and persistence to get either an internship or a job, and that does not end once you get it, either. Also, immerse yourself in learning new technologies and language; you become more marketable in the field.

Eunice Yeh

Undergraduate School: The University of North Carolina at Chapel Hill
Graduation Year: 2015
Position: Statistical Analyst/Programmer
Company: Harvard T.H. Chan School of Public Health
Sector: Health/Medicine

Background 
  • Bachelor of Science in Public Health from UNC Gillings School of Global Public Health
  • Biostatistics major, Mathematics minor
  • Relevant UNC courses: Linear Algebra, Real Analysis, Problem Analysis and Algorithm Design in Scientific Programming, Data Management in Clinical Trials, Statistical Computing, Probability and Inference, Regression Analysis, Sample Survey Methods
  • Assisted lab at UNC Department of Anesthesiology as a statistical analyst and SAS programmer
  • College Reading and Learning Association certified tutor in math and science at the University Tutorial Center at NC State University
Job Description

SAS programming, Unix environment, ODS RTF outputs, clinical trials, AIDS/HIV research

Statistics and Data Science at Work

My job is to provide statistical analysis with SAS programming support for studies involved in the AIDS Clinical Trials Group. This includes all aspects of work, from prediction models during study development through monitoring; descriptive statistics and hypothesis testing during interim, primary, and secondary analyses; and inference during the final dissemination of results.

Favorite Undergraduate Statistics Class

Intro to Biostatistics (BIOS500H) was my absolute favorite within my undergraduate experience at UNC. On top of being the optimal transitional course from the general education courses during my first years to the core requirements for my biostatistics degree, it was also a unique honors-level course that implemented the flipped-classroom style of learning. My professor presented the course materials in a very organized manner that supported our understanding of each topic and its relation with one another and then challenged our understanding not only through practice problems by hand, but also by programming in SAS. We left the course with fundamental knowledge of all statistical concepts useful in public health research and were prepared to dive deeper into each concept through the subsequent biostatistics courses in the program.

Advice for Students

You will find that statistics can be relevant to any career field you seek. As long as you are capable of generating and interpreting statistics, you will be able to exceed in any field of interest.

Dylan Quantz

Undergraduate School: Pomona College
Graduation Year: 2016
Position: Baseball Operations Trainee
Company: Atlanta Braves
Sector: Sports

Background

MS in data analytics (in progress)

Statistics and Data Science at Work

Analytics

Favorite Undergraduate Statistics Class

Clinical Trials

Advice for Students

If you want to work in sports, don’t ever give up. It may seem hard to get your foot in the door, but all it takes is that one team to take a chance on you.

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If you are a bachelor’s-level statistician interested in sharing your profile, please let us know.

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