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Company

Original Job Post

Harvard University · 3 days ago

Senior Data Scientist

Cambridge, MA

Full-time

Onsite

Senior Level

7+ years exp

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Responsibilities

Advise researchers in the design, planning, and implementation of data science workflows, tools, and pipelines.

Design and implement data set processes for data modeling and mining.

Assist with cloud computing-based infrastructure needs, data processing, and analytics.

Work with stakeholders to define multi-project plans for efficiency and transparency.

Build and maintain data science tools, data processing pipelines, and software code.

Develop advanced curriculum and teach workshops for researchers on data science practices.

Create custom solutions using specific technology to meet researcher’s needs.

Collaborate with developers and researchers in a team environment.

Provide regular project updates to stakeholders.

Abide by Harvard University IT technical standards, policies, and Code of Conduct.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

Data engineeringData architectureDatabase managementData visualizationNumerical methodsStatistical analysisMachine learningGlmGlmmSemEconometric modelsPythonRLinuxCloud platformsAmazon web servicesAwsEc2S3RedshiftLambdaSagemakerAthenaData warehousingEtl/elt processesSqlNosql databasesData modelingBig data technologiesHadoop

Required

Minimum of seven years’ post-secondary education or relevant work experience

Bachelor's or Master’s Degree in Statistics, Data Science, Computer Science, Mathematics, Informatics, or other health data related field

Prior work within a research environment is essential, including familiarity with the research pipeline and the process of conducting research employing accepted scientific experimental practices

Knowledgeable of data engineering, data architecture, database management, and data visualization techniques, with high proficiency in data extraction and wrangling

Numerical methods, statistical analysis, and machine learning. More specifically, experience fitting and interpreting a range of models, including at least some of: GLM, GLMM, SEM, econometric models, machine learning models

The ability to create and maintain databases using libraries from Python, R in Linux environment

Expertise in leveraging cloud platforms, especially Amazon Web Services (AWS), for scalable data processing and analytics (EC2, S3, Redshift, Lambda), and machine learning tools (SageMaker, Glue, Athena)

Experience with data warehousing and ETL/ELT processes. Skilled in SQL, NoSQL databases, and data modeling techniques. Experience with big data technologies and ecosystems (e.g. Hadoop, Spark)

CI/CD pipelines for data science projects and their reliable deployment. Assisting with release of models/products to the proper platform (e.g., a website, an interactive API, etc.), including infrastructure design

Background in scientific programming/scripting (Python, R, Stata, and C++); 3+ years of experience using either Python or R in a data science and/or research context required

Adherence to best practices in scientific programming, including version control (Git), code review, unit testing, and documentation to ensure reproducibility and maintainability of data science projects

Proven track record of success in working in a cross-functional team in an agile environment

Excellent communication skills; able to simplify complex technical concepts to stakeholders

Detail-oriented expertise, with strong problem-solving skills to support research

Strong team player with a service mindset, able to guide researchers and is customer focused

Awareness of and aptitude to appropriately and effectively understand, respect, and adapt to cultural and identity‐based difference within group environments, and experience fostering and reinforcing an environment that values unique experiences, cultures, backgrounds, and goals

Preferred

5+ years of experience using either Python or R in a data science and/or research context preferred. More specifically, advanced skills in Python libraries for data science (Pandas, NumPy, sci-kit learn, TensorFlow/PyTorch) or experience using object-oriented programming systems in R (e.g., S3, S4, RC, R6)

Completion of Harvard IT Academy specified foundational courses (or external equivalent) preferred

Benefits

Paid Time Off: 3-4 weeks of accrued vacation time per year

Health and Welfare: Comprehensive medical, dental, and vision benefits

Work/Life and Wellness: Child and elder/adult care resources, Employee Assistance Program, and wellness programs

Retirement: University-funded retirement plan with contributions from 5% to 15% of eligible compensation

Tuition Assistance Program: Competitive program including $40 per class at the Harvard Extension School

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