Data Scientist

23-May-2024

School of Public Health - Health Policy and Management

88423BR

University Job Title

Research Specialist

Bargaining Unit

None - Not included in the union (Yale Union Group)

If Fixed Duration, Period

1 year from date of hire

If Fixed Duration, is continuation possible?

Yes

Other Fixed Duration Date

30-Jun-2025

Compensation Grade

Clinical & Research

Compensation Grade Profile

Research Specialist (25)

Wage Ranges

Click here to see our Wage Ranges

Searchable Job Family

Administration

Total # of hours to be worked:

37.5

Work Week

Standard (M-F equal number of hours per day)

Work Location

Medical School Campus

Worksite Address

60 College Street
New Haven, CT 06510

Position Focus:

Yale School of Public Health (YSPH) is seeking a highly skilled Data Scientist (DS). This is a unique opportunity for a skilled programmer motivated to produce rigorous, empirical evidence to improve policy. The ideal candidate is an expert programmer fluent in R or Python, has experience manipulating health care datasets and working with advanced machine learning libraries (Scikit-learn, Keras, TensorFlow). Exceptional understanding of causal inference and a commitment to YSPH’s mission are crucial. The individual will analyze data to solve research questions using cutting-edge techniques. The individual will be embedded within DSS where they will work across teams and data systems to preform novel linkages between programs, enabling new research into previously unanswerable questions. As part of this, the DS will build new infrastructure to support advanced analytics and rigorous policy evaluations which can scale to accommodate the future needs of DSS.

The DS will develop and refine analytic plans with state-of-the-art statistical and econometric techniques to address research and quality improvement objectives at both Yale and DSS. They will develop novel predictive modelling capabilities within DSS using advanced machine learning techniques to improve the efficiency of current and future member-facing campaigns. After deployment, the DS will refine models with the goal of improving accuracy and targeting, and quantifying whether sophisticated techniques (e.g., deep learning) provide tangible benefits over current models.

In addition to possessing highly technical quantitative skills, the DS must be an expert communicator with the ability to explain technical analyses to non-technical stakeholders, and they will act as a project lead on a mutli-disciplinary team. The DS will lead the group’s ability to disseminate research findings. This includes distilling complicated research and designs down to succinct, impactful visualizations of results for academic papers and policy memos. The DS will lead in the drafting of manuscripts to ensure results are accurately and concisely communicated to the appropriate audience.

The DS will be the programming expert, mentoring team members, ensuring best practices in coding, and developing new tools to assure data integrity. They will be responsible for reviewing code of less senior members and will document best practices and mentor other team members in statistical methods. The DS will develop new tools and infrastructure to verify the integrity of data and will create quality assurance checks and unit tests to validate data extracts and analyses. The DS will create novel data sets as a result of never-before-done data linkages and will proactively lead public and private data acquisition campaigns.

The Position Focus above most accurately describes this role, while the Principal Responsibilities provides general context for all Data Scientist roles at Yale.

Principal Responsibilities include function as an embedded Data Scientist within DSS, collaborating across teams to create innovative data linkages that facilitate new research and policy evaluation. Design and construct a new data infrastructure from the ground up to support advanced analytics and comprehensive, scalable policy assessments. Conduct thorough data analysis to address specific research questions using state-of-the-art techniques.

Develop and refine predictive models within DSS to optimize efficiency and effectiveness of member services. Continuously improve these models post-deployment to enhance precision and efficacy. Lead efforts in communicating complex research findings through clear, effective visualizations and writings for various outputs such as academic papers, grant proposals, and policy briefs. Serve as a programming and data expert, mentoring team members, ensuring best practices in coding, and developing new analytic tools to assure data integrity.

Essential Duties

1. Coordinates and manages diverse survey and experimental research projects, including research design, questionnaire development, implementation, and analysis, working with a multi-institutional team of investigators. 2. Authors public reports and peer-reviewed publications. 3. Constructs and maintains large datasets, including codebooks. 4. Maintains an online library of research reports and articles. 5. Assists with grant proposals. 6. Disseminates research findings through briefings, presentations, and social media. 7. May perform other duties as assigned.

Required Education and Experience

Master’s degree in a relevant social science field or discipline, such as survey research, risk perception, communication (climate change, science, environment, public health, and/or political communication), behavior change, psychology, political science, sociology, or human geography and four years of experience or an equivalent combination of education and experience. Proficiency and experience in survey and experimental research, project and data management, and analysis.

Required Skill/Ability 1:

Demonstrated experience with programming languages like R or Python and familiarity with machine learning libraries.

Required Skill/Ability 2:

Strong communication skills with the ability to translate complex technical details into clear, actionable insights.

Required Skill/Ability 3:

Knowledge of social science research methods, causal inference, and statistics.

Required Skill/Ability 4:

Demonstrated experience manipulating large and complex datasets including Medicaid and health data.

Required Skill/Ability 5:

Strong interpersonal skills, communication skills, and the ability to interact well with faculty, staff, fellows, and research partners internally and externally.

Preferred Education, Experience and Skills:

Ph.D. in a quantitative field like Economics, Physics, Statistics, Mathematics, Data Science, Engineering, Health Policy or related fields. Health policy or health care research experience. Proven experience working with health data (especially Medicaid).

Weekend Hours Required?

No

Evening Hours Required?

No

Background Check Requirements

All candidates for employment will be subject to pre-employment background screening for this position, which may include motor vehicle, DOT certification, drug testing and credit checks based on the position description and job requirements. All offers are contingent upon the successful completion of the background check. For additional information on the background check requirements and process visit "Learn about background checks" under the Applicant Support Resources section of Careers on the It's Your Yale website.

COVID-19 Vaccine Requirement

The University maintains policies pertaining to COVID-19. All faculty, staff, students, and trainees are required to comply with these policies, which may be found here:
https://covid19.yale.edu/health-guidelines

Posting Disclaimer

The intent of this job description is to provide a representative summary of the essential functions that will be required of the position and should not be construed as a declaration of specific duties and responsibilities of the particular position. Employees will be assigned specific job-related duties through their hiring departments.

EEO Statement:

University policy is committed to affirmative action under law in employment of women, minority group members, individuals with disabilities, and protected veterans. Additionally, in accordance with Yale’s Policy Against Discrimination and Harassment, and as delineated by federal and Connecticut law, Yale does not discriminate in admissions, educational programs, or employment against any individual on account of that individual’s sex, sexual orientation, gender identity or expression, race, color, national or ethnic origin, religion, age, disability, status as a special disabled veteran, veteran of the Vietnam era or other covered veteran.

Inquiries concerning Yale’s Policy Against Discrimination and Harassment may be referred to the Office of Institutional Equity and Accessibility (OIEA).

Note

Yale University is a tobacco-free campus