Full-Stack Machine Learning Engineer/Data Scientist
Role details
Job location
Tech stack
Job description
Participate in the design of software that supports and enriches research productivity and reliability; implement software solutions. Develop software and data services with researchers to ensure that modern standards of reproducible code are kept. Job-Specific Responsibilities
Lead analytic development across several ongoing clinical research initiatives and enrich research productivity and reliability; implement software solutions. Ensure that modern standards of reproducible code are kept., * Work with the research team to support the design, development, and implementation of ML models.
- Support infrastructure for cleaning, processing, analyzing, and visualization of various data types (eg, GPS data scraped from smartphones, accelerometer data from wearable devices, digital phenotyping data, etc.).
- Support experiments to evaluate model performance, perform error analysis, and suggest and implement improvements.
- Conduct higher-level analysis of data and supervise analyses performed by other members of the lab.
- Integrate data across workflows (eg, digital phenotyping, behavioral, and clinical data).
- Help to develop and support a secure, scalable dashboard or lightweight clinical app that synthesizes data and provides visualizations in real-time.
- Deploy modular, reusable visualization components and maintain version-controlled code repositories.
- Work closely with university and Harvard teaching hospital-based IT teams to ensure interoperability, reliability, and clinical relevance.
- Assist with preparation of grant applications, presentations, and publications.
Requirements
- Minimum of five years' post-secondary education or relevant work experience., * 3-5+ years of hands-on experience with time-series data, sensor data, or biomedical/wearable data.
- Proficiency in one or more programming languages (Python and/or JavaScript preferred), including libraries for ML (TensorFlow, PyTorch), data engineering (pandas, NumPy), and visualization (Plotly, Dash, Bokeh).
- Experience deploying dashboards or apps (eg, Dash, Streamlit, React, Flask, or similar).
- Experience with Real Time or streaming data pipelines.
- Expert-level knowledge of statistical programming, particularly R (tidyverse, ggplot2) and R Markdown.
- Strong understanding of ML approaches for classification, anomaly detection, and prediction using high-frequency data.
- Experience with multilevel longitudinal data, missing data strategies, and clinical outcome modeling.
- Experience with EHR data, REDCap, Qualtrics, or hospital-based informatics systems.
Certificates and Licenses
- Completion of Harvard IT Academy specified foundational courses (or external equivalent) preferred.
Benefits & conditions
Occasionally required to work outside of normal business hours, and may be contacted during off hours., Standard Hours/Schedule: 35 hours per week. Visa Sponsorship Information: Harvard University is unable to provide visa sponsorship for this position. Pre-Employment Screening: Identity, Criminal. This is a one-year term position with renewal dependent upon continuation of funding. All formal offers will be made by FAS Human Resources. Work Format Details
This position has been determined by school or unit leaders that some of the duties and responsibilities can be effectively performed at a non-Harvard location. The work schedule and location will be set by the department at its discretion and based upon operational needs. When not working at a Harvard or Harvard-designated location, employees in hybrid positions must work in a Harvard registered state in compliance with the University's Policy on Employment Outside of Massachusetts. Additional details will be discussed during the interview process. Certain visa types and funding sources may limit work location. Individuals must meet work location sponsorship requirements before employment. Salary Grade and Ranges
This position is salary grade level 057. Please visit Harvard's Salary Ranges to view the corresponding salary range and related information. Benefits
- Generous paid time off including parental leave.
- Medical, dental, and vision health insurance coverage starting on day one.
- Retirement plans with university contributions.
- Well-being and mental health resources.
- Support for families and caregivers.
- Professional development opportunities including tuition assistance and reimbursement.
- Commuter benefits, discounts and campus perks.
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