UW Biostatistics Master of Science Capstone students had the opportunity to strengthen and build their professional portfolios this past summer through a variety of different internship experiences.
Helping students gain relevant, real-world experience is a key focus of the 18-month MS Capstone program.
"An internship is a perfect opportunity to learn more about the industry you're interested in, build your connections, talk to people in the roles that you're curious about, learn about their career path, get advice from people and make new friends,” said Yingying Wei, a student who interned as a data scientist with the Product Development Data Sciences Department at Genentech, Inc.
Lester Tsai, who worked as a credit modeler at Conn’s Inc., gained an "understanding of how to collaborate with other colleagues in a fast-paced environment, how to seek help from others when facing problems, and practice what I’ve learned from school this past year."
Katie McFarlane appreciated the chance to put classroom knowledge to use in a practical setting.
“I’ve enjoyed working with real life data and dealing with missing data. It’s been valuable to experience a project from beginning to end, including times when data is not available or comes with limitations, and learning how to analyze this information in meaningful ways has been exciting,” said McFarlane who served as an evaluation and analytics intern with OCHIN, a nonprofit health care innovation center designed to provide knowledge solutions that promote quality, affordable health care for all.
Internships also helped students to develop skills and gain new insights
Howard Baek, a biostatistics intern with Merck, found communication skills to be particularly valuable.
“It is really important to know what your stakeholders are asking for, what roadblocks you are facing, and what value the software you built provides,” said Baek.
“I learned more clinical trials details from a business perspective, especially in drug development,” said Han Liu, a biostatistics intern with Cytel, a company that provides statistical software and advanced analytics for clinical trial design and execution.
2022 MS Capstone Summer Internships
Howard Baek
- Capstone pathway: Data Science
- Internship: Biostatistics Intern, Biostatistics & Research Decision Sciences, Merck
- Responsibilities: Built an open-source R package for querying Clinicaltrials.gov and consolidating analysis datasets. Also, programmed an internal R Shiny app to provide Merck users an easier interface to the R package.
Eliza Chai
- Capstone pathway: Data Science
- Internship: Research Database Development Intern, Research & Development, BioMarin
- Responsibilities: Developed database tracking tools for experimental plate-based assays with Excel VBA codes to manage sourcing efforts within the Research and Early Development department. Queried and connected SQL database to TIBCO SpotFire to design research dashboards and implement R, python scripts within SpotFire for data analysis and scientific visualization in early drug development
Han Liu
- Capstone pathway: Methods & Modeling
- Internship: Biostatistics Intern, Data Monitoring Committee Group, Cytel
- Responsibilities: Reviewed ICH (Efficacy and Safety) documents which are used by FDA (e.g., clinical study reports and statistical principles for clinical trials).
Ingrid Luo
- Capstone pathway: Data Science
- Internship: Biostatistics Intern, Research & Development, Nanostring
- Responsibilities: Supported the computational team in developing a suite of statistical and visualization tools for single-cell RNA-seq analysis and data correctness tests.
Katie McFarlane
- Capstone pathway: Data Science
- Internship: Evaluation & Analytics Intern, OCHIN
- Responsibilities: Assisted with rapid analysis projects regarding health equity, as well as other ad hoc projects, such as conducting R workshops and analyzing company surveys.
Makayla Tang
- Capstone pathway: Data Science
- Internship: Bioinformatics Data Scientist Intern, Department of Genome Sciences, University of Washington
- Responsibilities: Analyzed the differential gene expression between the diabetes cells and the normal cells by R programming.
Lester Tsai
- Capstone pathway: Data Science
- Internship: Credit Card Modeler, Credit Team, Conn’s Inc.
- Responsibilities: Implemented XGBoost in Python and SAS Viya to decide on client loan approval. Using model tuning and validation techniques, our result indicates that the accuracy of our model reaches over 0.7. Accelerated computation speed by building pipelines in PySpark, saving 10% time compared to Pandas. Communicated the results with critical decision-makers before launching the model deployment. Determined the existence of fraud among applicants from the SentiLink platform.
Thu Vu
- Capstone pathway: Data Science
- Internship: DMC Biostatistician, Project-Based Services, Cytel
- Responsibilities: Support Data Monitoring Committees (DMCs) by reviewing blinded and unblinded data reports of clinical trials and providing feedback to the Lead Statistician. We discussed and interpreted adverse event, laboratory, and interim data. Additionally, participated in trial design discussions about protocols, statistical/interim analysis plans, and sample size calculations.
Hanyi Wang
- Capstone pathway: Methods & Modeling
- Internship: Research Assistant, Center for Computational Biology and Bioinformatics, Columbia University
- Responsibilities: Collected and annotated de novo and rare missense variants in NOTCH1 and other genes in the NOTCH family. Used machine learning, protein structure, and phenotypes to optimize the interpretation of missense variants in these genes in CHD and associated disorders.
Yingying Wei
- Capstone pathway: Methods & Modeling
- Internship: Data Scientist, Product Development-Data Sciences, Genentech
- Responsibilities: Worked on different modules for Rshiny apps, including enhancement based on requests from the study team, authorization and deployment of the app, etc.
Learn more about the UW Biostatistics MS Capstone Program
