Data Science Mentoring Circles Program

Call for Student Mentee Applications!

Application Deadline: Friday, September 19th, 2025, at midnight
How to Apply: See the ‘Apply to be a mentee’ link below.

Are you ready to turn your academic knowledge into a career in Data Science, Machine Learning, or Data Analytics? In today’s competitive job market, the Data Science Mentoring Circles (DSMC) program is designed to give you a distinct advantage. The DSMC program provides the personalized guidance you need to stand out.

As a mentee, you will receive:

One-on-One Resume Crafting: Work directly with an industry professional to build a resume that gets noticed.
Targeted Interview Prep: Participate in discussions and mock interviews to build the confidence to ace your interviews.
Exclusive Network Access: Join a private LinkedIn group connecting you with all DSMC mentors and mentees since 2020. Learn directly from professionals at industry leaders like Google, Meta, Amazon, Microsoft, Etsy, CVS, and Accenture.

Explore our 2025 mentors’ slate and hear about past participants’ experiences to see where this journey can take you!

View events link below to learn more about the activities of this free program with limited spots.

Have Questions? Join one of our info sessions led by Ranfei Xu (ranfeixu@bu.edu), MBTA Program Analyst, to learn more and network. See details below.

In-Person Meetup:

Meet past and potential mentees, network, and hear Ranfei share mentoring styles and what mentors look for. She’ll also answer your questions to help you find the best match.

Date: Tuesday, September 16, 2025
Time: 6:00 – 7:00 PM ET
Location: 665 Commonwealth Avenue, Room 1101

Boston University is committed to the highest levels of intellectual and creative achievement. Crucial to that mission is a significantly increased breadth of social, cultural, racial, and ethnic diversity among our ranks. We strongly encourage applications from diverse candidates for both mentors and mentees.

Events

Mentor & Mentee Eligibility

Apply to be a Mentor

Mentors should be industry professionals with at least two years of experience working in either Data Science, Machine Learning, Biostatistics, or Statistics.

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Need inspiration? Check out previous mentors biographies!
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Consent*
I certify that I am age 18 or older and have read the terms, fully understand the contents thereof, and agree to these terms.
I understand that Boston University (BU) is interested in recording [my lecture/speech/poetry reading/ performance/symposium, etc.](my "Content") and presenting it on the BU Rafik B. Hariri Institute for Computing and Computational Science & Engineering social media accounts and websites. In connection with my participation in the Data Science Mentor Circles program, I grant to Boston University the following rights and permissions:

1. To record, by any means, including without limitation audiotape, videotape, and photograph, my voice and image and any speech, text, image, or other content I present (the “Recordings”).

2. To reproduce, edit, display, telecast, podcast, webcast, stream, distribute, and otherwise use the Recordings or any portion thereof, and to identify me in connection therewith, for University-related and other educational purposes. Any editing will be for technical and presentation purposes only and will not alter the substance of the Recordings.

Except for permissions expressly granted to the University herein, I shall retain all right, title and interest to my Content. The University shall have all right, title, and interest in and to the Recordings. I release and discharge the University and its employees and agents from all claims and demands arising out of, or in connection with, the use of such Recordings but only to the extent the University does not alter the substance of the Recordings and only to the extent the Recordings are used for noncommercial University-related educational purposes.

I grant the above permissions irrevocably and without payment of fee or royalty.

Meet Past Participants' Mentors

David Liu, PhD, Class of 2001
Senior Director of Global Data Science and Analytics, Keurig Dr Pepper

David has over 20 years of experience working in ML, AI Modeling, and Analytics.

Currently, David is the Sr. Director of Global Data Science and Analytics at Keurig Dr Pepper (KDP). He leads a team of Data Scientists and Machine Learning Engineers to develop ML and optimization solutions at enterprise level, supporting multiple business units (i.e. Supply Chain, Manufacture, Direct Store Delivery Operation, Commercial).

Prior to joining KDP in 2021, David served at CVS Health for 5 years, leading two AI/ML driven personalization initiatives to drive business growth at Front Store and Retail Pharmacy business areas. Before CVS, David spent 15 years in the Financial Services industry developing analytical solutions for marketing purposes, fraud detection, and risk analysis.

Clementine Plati, PhD, Class of 2018
Staff Machine Learning Scientist, Etsy

Clementine is a Staff Machine Learning Scientist at Etsy. From within their Recommender Systems team, she leads the development and productionalization of models that aim to provide a personalized experience to visitors.

Prior to joining Etsy, Clementine spent a couple years at Twitter as Machine Learning Researcher where she worked on developing the next generation of recommender systems. Among other things, her models were launched on the Who-To-Follow and notifications products. She also worked at Tripadvisor where she refined the models the company uses to automate its online marketing strategies.

Clementine holds a Ph.D. in Statistics from Boston University and a Master’s degree in Applied Mathematics from the INSA of Toulouse, France. Over the years, she has held leadership positions in various non-profit organizations such as the Massachusetts Association for Women in Science (MASS AWIS), the Boston University’s Graduate Association for Women in Science (GWISE@BU), and the Boston University Student Chapter of the ASA (BUSCASA). Currently, she is serving on the council of the New England Statistical Society (NESS) and is a key leader of the Boston University’s Data Science Mentoring Circles which she co-founded in 2020.

Xiaoyu Jiang, PhD, Class of 2009
Director of Biostatistics, Sanofi

Doctor Xiaoyu Jiang has been working in the pharmaceutical industry for 11 years, with broad experiences in all phases of drug development. As the Director of Biostatistics at Sanofi, she is leading the global submission of sutimlimab in Cold Agglutinine Disease, and the late phase clinical development for several compounds in the rare blood disorders. Prior to Sanofi, she worked at Biogen as an Associate Director in the aducanumab program for Alzheimer’s disease, and in a few post-approval programs in Multiple Sclerosis. She has also spent years in Merrimack pharmaceuticals, Novartis and Boehringer-Ingelheim, working on early phase clinical studies in oncology, translational research in psoriasis, rheumatoid arthritis and chronic kidney disease.

Xiaoyu received her PhD in Statistics from the Department of Mathematics and Statistics in Boston University in 2009. She has been interested and involved in the pharma-academic collaboration – she has given three talks at the Statistics at Work Seminar series in the MSSP program at BU. She is looking forward to bringing her knowledge and experience to this mentorship program.

Carlos J. Morales, PhD, Class of 2002
Director Global Portfolio Strategy, Liberty Mutual Investments

Carlos is a Director in the Strategy and Asset Allocation group at Liberty Mutual Investments (LMI). He leads the multi-asset class research including fixed income securities, public equities, private equity, and real assets. He developed and implemented a customized asset allocation framework based on scenario analysis which is the basis of the CIO yearly asset class recommendation for the totality of assets managed. He works closely with investment teams across the organization to ensure alignment of ideas and foster collaboration.

Carlos’ career spans over 20 years of experience in the financial industry in various capacities. He was a senior quantitative analyst in State Street Global Advisors, leading research and contributing trading ideas in quantitative credit. Carlos was part of the Wellington Management fixed income quant team, and developed innovative solutions pertaining to liquidity risk and a mew Equity/High Yield bond strategy. As a quantitative investor at GMO LLC, he ran a novel quantitative portfolio for corporate bonds in the company’s hedge fund. Carlos has published several peer reviewed journal articles, and he is a regular contributor as white paper author in investment topics. He holds joint BAs in Mathematics and Philosophy from University of Houston, and a PhD in Mathematics from Boston University. He was an associate Professor of mathematics at Worcester Polytechnic Institute.

Carlos has served as finance chair on the Lesley Ellis School board, as chair of a national award committee in the American Statistical Association. Carlos is a pianist, and he enjoys playing solo or in bands in local venues.

Lily Lavitas, PhD, Class of 2018
Senior Data Scientist, Tripadvisor

Lily graduated from Boston University with a Ph.D. in Statistics in 2018. Upon graduation, she joined Amazon as a Research Scientist in the Alexa Machine Learning department where she was working on internalization of Alexa devices building natural language models for pre-production languages, such as Spanish, French and Hindi.

Lily is now working as a Senior Data Scientist at Tripadvisor, being responsible for building and deployment of recommender system models. These models define sorting algorithms for hotels and restaurants on Tripadvisor’s website and support users in their travel planning. In her free time, she enjoys spending time with her husband and two daughters.

Ran Tao, M.S, Class of 2020
Senior Data Scientist, Wayfair

Ran graduated from Boston University with a Master in Statistics in 2019 and joined the Data Science team at Wayfair. She has been leading a machine learning work stream at Wayfair by building a real-time bidding model for online social and display ads. She collaborated with the engineering team and marketing team to implement her model in a real-time environment, helping generate millions of incremental revenue/year.

Ran has a strong background in statistical analysis and machine learning, especially in the area of customer value prediction, customer behavior pattern encoding, and customer segmentation.