Full-Stack Machine Learning Engineer / Data Scientist
Harvard University
•
Cambridge, MA
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0
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Not Applicable
Posted March 14, 2026
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Responsibilities
Commitments
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 (e.g., 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 (e.g., 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.
Commitments
This role is ideal for someone who wants to work on mental health research with real-world implications.
Working 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
Other Information: 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 prior to employment.
This position is salary grade level 057.
Not Met Priorities
What still needs stronger evidence
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 (e.g., 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.
Preferred Skills
- 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 (e.g., 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
Education
- (Required) – Minimum of five years’ post-secondary education or relevant work experience
- (Not required) – Completion of Harvard IT Academy specified foundational courses (or external equivalent) preferred
Company Description
By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.
Why join the Harvard Faculty of Arts and Sciences?
The Faculty of Arts and Sciences (FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs (the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences, founded in 1872), Harvard Athletics and the Division of Continuing Education. The 40 academic departments and 30+ centers of the FAS support a community unparalleled in its academic excellence across the broadest range of liberal arts and sciences disciplines. Together, the FAS seeks to foster an environment of ambition, curiosity and shared commitment to knowledge and truth that elicits excellence from all members of our community and prepares the next generation of leaders through a transformative educational experience.
Job Description
Job Summary:
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.
A research lab studying suicide in the Department of Psychology at Harvard University is seeking to hire a Full-Stack Machine Learning Engineer (MLE) / Data Scientist (DS) to support the end-to-end management, analysis, and visualization of behavioral and clinical data streams. The full-stack MLE/DS will work on studies aimed at advancing the understanding, prediction, and treatment of suicidal thoughts and behaviors. The position involves working on scalable data pipelines, integrating multimodal data (e.g., data from smartphone-based surveys, passive smartphone/wearable monitors, social media platforms, electronic health records), and helping to deploy analytic tools that can generate actionable insights (e.g., visualizations, algorithms) in real-time.
The MLE will join a dynamic, multi-site team working at the intersection of machine learning, digital phenotyping, pediatric mental health, and real-time clinical decision support on projects aimed at improving identification of, and intervention on, mental health problems (e.g., suicide) using rich data sources. The successful applicant will have strong programming skills and technical expertise in ML to execute tasks independently, advanced data management, analysis, and visualization skills. This role is ideal for someone who wants to work on mental health research with real-world implications. Responsibilities include:
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 (e.g., 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 (e.g., 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.
Working Conditions:
Occasionally required to work outside of normal business hours, and may be contacted during off hours
Qualifications
Basic Qualifications:
Minimum of five years’ post-secondary education or relevant work experience
Additional Qualifications and Skills:
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 (e.g., 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
Additional Information
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
Other Information: 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 prior to 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
Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to:
Generous paid time off including parental leave
Medical, dental, and vision health insurance coverage starting on day one
Retirement plans with university contributions
Wellbeing and mental health resources
Support for families and caregivers
Professional development opportunities including tuition assistance and reimbursement
Commuter benefits, discounts and campus perks
Learn more about these and additional benefits on our Benefits & Wellbeing Page.
EEO/Non-Discrimination Commitment Statement
Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.
Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.
By working at Harvard University, you join a vibrant community that advances Harvard's world-changing mission in meaningful ways, inspires innovation and collaboration, and builds skills and expertise. We are dedicated to creating a diverse and welcoming environment where everyone can thrive.
Why join the Harvard Faculty of Arts and Sciences?
The Faculty of Arts and Sciences (FAS) is the historic heart of Harvard University. It is the home of Harvard’s undergraduate program (Harvard College, founded in 1636) as well as all of Harvard’s Ph.D. programs (the Harvard Kenneth C. Griffin Graduate School of Arts and Sciences, founded in 1872), Harvard Athletics and the Division of Continuing Education. The 40 academic departments and 30+ centers of the FAS support a community unparalleled in its academic excellence across the broadest range of liberal arts and sciences disciplines. Together, the FAS seeks to foster an environment of ambition, curiosity and shared commitment to knowledge and truth that elicits excellence from all members of our community and prepares the next generation of leaders through a transformative educational experience.
Job Description
Job Summary:
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.
A research lab studying suicide in the Department of Psychology at Harvard University is seeking to hire a Full-Stack Machine Learning Engineer (MLE) / Data Scientist (DS) to support the end-to-end management, analysis, and visualization of behavioral and clinical data streams. The full-stack MLE/DS will work on studies aimed at advancing the understanding, prediction, and treatment of suicidal thoughts and behaviors. The position involves working on scalable data pipelines, integrating multimodal data (e.g., data from smartphone-based surveys, passive smartphone/wearable monitors, social media platforms, electronic health records), and helping to deploy analytic tools that can generate actionable insights (e.g., visualizations, algorithms) in real-time.
The MLE will join a dynamic, multi-site team working at the intersection of machine learning, digital phenotyping, pediatric mental health, and real-time clinical decision support on projects aimed at improving identification of, and intervention on, mental health problems (e.g., suicide) using rich data sources. The successful applicant will have strong programming skills and technical expertise in ML to execute tasks independently, advanced data management, analysis, and visualization skills. This role is ideal for someone who wants to work on mental health research with real-world implications. Responsibilities include:
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 (e.g., 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 (e.g., 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.
Working Conditions:
Occasionally required to work outside of normal business hours, and may be contacted during off hours
Qualifications
Basic Qualifications:
Minimum of five years’ post-secondary education or relevant work experience
Additional Qualifications and Skills:
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 (e.g., 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
Additional Information
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
Other Information: 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 prior to 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
Harvard offers a comprehensive benefits package that is designed to support a healthy work-life balance and your physical, mental and financial wellbeing. Because here, you are what matters. Our benefits include, but are not limited to:
Generous paid time off including parental leave
Medical, dental, and vision health insurance coverage starting on day one
Retirement plans with university contributions
Wellbeing and mental health resources
Support for families and caregivers
Professional development opportunities including tuition assistance and reimbursement
Commuter benefits, discounts and campus perks
Learn more about these and additional benefits on our Benefits & Wellbeing Page.
EEO/Non-Discrimination Commitment Statement
Harvard University is committed to equal opportunity and non-discrimination. We seek talent from all parts of society and the world, and we strive to ensure everyone at Harvard thrives. Our differences help our community advance Harvard's academic purposes.
Harvard has an equal employment opportunity policy that outlines our commitment to prohibiting discrimination on the basis of race, ethnicity, color, national origin, sex, sexual orientation, gender identity, veteran status, religion, disability, or any other characteristic protected by law or identified in the university's non-discrimination policy. Harvard's equal employment opportunity policy and non-discrimination policy help all community members participate fully in work and campus life free from harassment and discrimination.