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jobs description

Auto req ID


Job Code

I1257P IT RC Software/Data Prof III

Department Office Location

USA - MA - Cambridge

Business Title

Machine Learning Engineer


Social Sciences

Salary Grade


Time Status



00 - Non Union, Exempt or Temporary

Additional Qualifications and Skills
• Ph.D. or Master’s Degree in Computer Science, Data Science,
Electrical Engineering, Mathematics, Statistics, Psychology, or
related field.
• Expertise in one or more programming languages (Python and/or
JavaScript preferred).
• Prior applied experience designing and developing ML
• 5+ years of data management and analysis experience.
• Experience cleaning and analyzing digital phenotyping
• Advanced statistical skills including expertise with
longitudinal data analysis (e.g., multilevel modeling) and
strategies for dealing with missing data.
• Experience with toolkits such as TensorFlow, PyTorch, or
• Demonstrated history of commitment to open science and
reproducible science (e.g., via an active Github or OSF page).
• Expert-level knowledge of statistical programming, particularly
R (tidyverse, ggplot2) and R Markdown.
• Experience with of survey software, REDCap and Qualtrics.
• Ability to troubleshoot, optimize, and manage small and large
projects with different timelines.
• Ability to work closely with people with a range of statistical
programming knowledge (from undergraduates to other experts).
• Ability to carefully consider conflicting demands of
confidentiality of sensitive data and open science.
• Ability to work independently with minimal supervision, but
also function well as part of a team, have excellent formal and
interpersonal communication skills, and the ability to communicate
technical information effectively to a broad range of
• Lab experience and/or coursework on self-injury and suicidal

Additional Information

This is a one-year term position with renewal dependent upon
continuation of funding.

We regret that we will not be able to provide visa sponsorship for
this position.

All formal offers will be made by FAS Human Resources.



Pre-Employment Screening

Criminal, Identity

Job Function

Information Technology


Faculty of Arts and Sciences

EEO Statement

We are an equal opportunity employer and all qualified applicants
will receive consideration for employment without regard to race,
color, religion, sex, national origin, disability status, protected
veteran status, gender identity, sexual orientation, pregnancy and
pregnancy-related conditions, or any other characteristic protected
by law.

Basic Qualifications
• Minimum of five years’ post-secondary education or relevant
work experience

Working Conditions
• Occasionally required to work outside of normal business hours,
and may be contacted during off hours

Position Description

Matthew K. Nock, the Director of the Nock Lab in the Department of
Psychology at Harvard University is seeking to hire a Machine
Learning Engineer (MLE) / Data Scientist (DS) with expertise in
machine learning (ML) and the management and analysis of data. The
MLE/DS will work on studies aimed at advancing the understanding,
prediction, and treatment of suicidal thoughts and behaviors. The
data to be managed and analyzed are from smartphone-based surveys,
passive smartphone/wearable monitors, and social media platforms.
The MLE will clean, transform, and merge data and will run advanced
data analyses.

The MLE will work with a dynamic, multi-site team 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, sufficient
knowledge, and technical expertise in ML to execute tasks
independently, advanced data management and analysis skills, and
interest in application of ML to the healthcare sector. In addition
to designing and developing ML models, the MLE will:
• Work with the research team to design, develop, and implement
ML models.
• Create and assist in development of 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.).
• Run 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).
• Program behavioral tasks and archive studies.
• Assist with preparation of grant applications, presentations,
and publications.

Commitment to Equity, Diversity, Inclusion, and

Harvard University views equity, diversity, inclusion, and
belonging as the pathway to achieving inclusive excellence and
fostering a campus culture where everyone can thrive. We strive to
create a community that draws upon the widest possible pool of
talent to unify excellence and diversity while fully embracing
individuals from varied backgrounds, cultures, races, identities,
life experiences, perspectives, beliefs, and values.


We invite you to visit Harvard's Total Rewards website ( https://hr.harvard.edu/totalrewards ) to learn more
about our outstanding benefits package, which may include:
• Paid Time Off: 3-4 weeks of accrued vacation time per
year (3 weeks for support staff and 4 weeks for
administrative/professional staff), 12 accrued sick days per year,
12.5 holidays plus a Winter Recess in December/January, 3 personal
days per year (prorated based on date of hire), and up to 12 weeks
of paid leave for new parents who are primary care givers.
• Health and Welfare: Comprehensive medical, dental, and
vision benefits, disability and life insurance programs, along with
voluntary benefits. Most coverage begins as of your start
• Work/Life and Wellness: Child and elder/adult care
resources including on campus childcare centers, Employee
Assistance Program, and wellness programs related to stress
management, nutrition, meditation, and more.
• Retirement: University-funded retirement plan with
contributions from 5% to 15% of eligible compensation, based on age
and earnings with full vesting after 3 years of service.
• Tuition Assistance Program: Competitive program
including $40 per class at the Harvard Extension School and reduced
tuition through other participating Harvard graduate schools.
• Tuition Reimbursement: Program that provides 75% to 90%
reimbursement up to $5,250 per calendar year for eligible courses
taken at other accredited institutions.
• Professional Development: Programs and classes at little
or no cost, including through the Harvard Center for Workplace
Development and LinkedIn Learning.
• Commuting and Transportation: Various commuter options
handled through the Parking Office, including discounted parking,
half-priced public transportation passes and pre-tax transit
passes, biking benefits, and more.
• Harvard Facilities Access, Discounts and Perks: Access
to Harvard athletic and fitness facilities, libraries, campus
events, credit union, and more, as well as discounts to various
types of services (legal, financial, etc.) and cultural and leisure
activities throughout metro-Boston.

Work Format


Work Format Details

This position is based primarily on-campus, in Massachusetts. This
may include in-person during emergency situations (if applicable).
Additional details will be discussed during the interview process.
Certain visa types may limit work location. Individuals must meet
work location sponsorship requirements prior to employment
Cambridge MA United States


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