Max Melnikas

Max Melnikas

Master of Science Candidate

Harvard Chan School of Public Health

Biography

Hello and welcome to my personal website! I am an aspiring biostatistician interested in incorporating digital technologies into healthcare systems for monitoring health and tracking disease progression. As a master’s degree candidate at the Harvard Chan School of Public Health Department of Biostatistics, I have developed a multifaceted skill set of quantitative methods. I currently work on JP Onnela’s team where I support Beiwe - a research platform that gathers and analyzes physical and other data from participants’ iOS and Android mobile devices. In May of 2023, I graduated from Brandeis University with two Bachelors of Science in Neuroscience and Biology and minors in Computer Science and Chemistry. I grew up in Moscow, Russia, attending the Anglo American School of Moscow and graduating with an International Baccalaurreate diploma.

Interests
  • Digital Health
  • Statistical Learning
  • Missing Data
Education
  • MS in Biostatistics, 2025

    Harvard Chan School of Public Health

  • BS in Neuroscience and Biology, 2023

    Brandeis University

Skills

Technical
Machine Learning
Survival Analysis
Longitudinal Analysis
Exploratory Data Analysis
Data Mining
Data Visualization
Data Wrangling
Computer Vision
Computational Neuroscience
Program Automation
Object-Oriented Programming
Software
R
Python
Git and Github
Excel
Matlab
Unix
Anaconda
Java
PowerPoint
Redcap
AlignMix

Experience

 
 
 
 
 
Research Assistant
September 2023 – Present Massachusetts
  • Provided study support to 10+ external research teams using Beiwe to capture digital health data streams (accelerometer, GPS, active surveys and audio recordings) using iOS and Android apps on participants’ mobile devices
  • Maintained the open-source, python-based Forest package that converts raw Beiwe data into individual and cohort-wide summaries for the four passive and active data streams mentioned above
  • Conducted audits of Beiwe app performance and quantified impacts of app updates on data quality and longevity
  • Demonstrated usage of the Forest package to research teams and worked to resolve any issues that arose
  • Identifed new software bugs to the development team and shared resolutions to the research teams running studies
 
 
 
 
 
Summer Associate Consultant
June 2024 – August 2024 Massachusetts
  • Analyzed claims data of ~60k HCPs and identified 5,000 top promotional targets for a rare-oncology product launch
  • Modeled several field team structures using a series of workload assumptions to generate a final sizing of 35 field reps
  • Aligned the US into 35 territories rolled up into 5 regions, ensuring adequate workload and transportation access for reps
  • Generated content and synthetic sales data for a demo of a pharmaceutical field team incentive compensation solution
 
 
 
 
 
Teaching Assistant
August 2020 – December 2022 Massachusetts
  • Designed a procedure for an online, simulation-based chemistry laboratory experiment during the pandemic, when chemistry lab was offered only remotely
  • Led laboratory sessions and recitations for groups of 20+ chemistry laboratory students
  • Provided one-on-one tutoring, coding support and feedback for programming assignments and problem sets of students in data structures and discrete mathematics
 
 
 
 
 
Research Intern
June 2022 – August 2022 Massachusetts
  • Proposed a standardized home-based tES protocol as part of a written review of previously published literature
  • Assisted in T-test statistical analysis for a multi-site aging study that provided patients with personalized health insights
  • Recruited participants and observed lab and home-based screenings for cognition and mobility

Projects

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Car Market Analysis: Finding High Discount Listings
An automated pipeline that gathers daily car listing data through an API and notifies of cars with discounts.
Pathos: Associations of Word Usage and Emotions
Analyzing text patterns using the Apriori algorithm and drawing associations with emotions using logistic regression
Sweet Dreams: A Regression Analysis of Macronutrient Intake and Sleep Quality
Exploring various sleep quality endpoints with multiple, logistic, multinomial and Poisson regressions

Certificates

Biomedical Research Investigators
See certificate
Social & Behavioral Research Investigators
See certificate
Biomedical Responsible Conduct of Research
See certificate

Recent & Upcoming Talks

Contact

Let’s connect! Feel free to drop me a message — would be excited to hear from you.