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Research Associate/Data Analyst
4 months ago
Title: Research Associate/Data Analyst
School: Harvard School of Dental Medicine
Department_Area: Oral Health Policy and Epidemiology
Position Description: We seek a Research Data Analyst in the Department of Oral Health Policy and Epidemiology ( OHPE ). This position will involve working with
PIDr. Hawazin Elani on various health policy and machine learning projects focused on disparities in oral health.
This position's responsibilities include managing multiple projects including large tabular datasets, estimating statistical models, determining and writing statistical considerations and algorithms and managing and maintaining documentation of files and analyses.
This analyst will summarize and present findings as reports, tables, graphs, and models, and will collaborate with the team on manuscripts, abstracts, and other publications presenting study findings.
The person will be responsible for completion of these tasks within project timelines and must ensure the integrity of data collection, review, compilation, and analysis techniques.
The analyst must follow proper procedures for working with confidential data in compliance with institutional and regulatory guidelines, including staying current with training requirements related to human subject research and data security.
This job is perfect for someone with a passion for practical research, the ability and willingness to acquire new skills, and the ability to take the lead as projects progress.
Duties and responsibilities include but are not limited to, the following data analysis and programming tasks:
- Develop Machine Learning Models to analyze large datasets.
- Data Management and Analysis (use statistical methods to interpret and validate data results).
- Document model development, structure, logic, coding, and testing.
- Engage in research dissemination activities, including presentations at lab meetings and regular updates to funding agencies.
- Contribute to developing new projects and proposals.
- Able to work independently and collaboratively with other research team members.
- Abide by and follow the Harvard University IT technical standards, policies, and Code of Conduct.
- Manage logistical and administrative aspects of the project; compliance with budgetary and reporting requirements; compliance with IRB submissions and revisions.
- Bachelor's degree in computer science, data science, statistics, or a closely related field with 2+ years of relevant experience.
- Proficiency in programming languages such as Python or R.
- Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).
- Experience with data manipulation and analysis using SQL and data visualization tools.
- Experience with big data tools (e.g., Spark).
- Ability to work independently with minimal supervision and as a team member.
- Strong problem-solving organizational skills and attention to detail.
- Excellent communication and collaboration skills.
- Experience and knowledge of machine learning, desirable expertise in causal inference and econometric analyses.
- Master's degree or Ph.
- Experience analyzing health and environmental data, including electronic health records, administrative claims (such as Medicare, Medicaid, and private insurance plans), and national survey data, is strongly preferred.
- Familiarity with cloud computing platforms.
- Strong quantitative background, experience working with large data sets and data management
Working Conditions:
Work is performed in an office setting. Individual hybrid work options for this role will be discussed during the interview process.
Contact Information: Hawazin Elani
188 Longwood Avenue
Boston, MA 02115
Contact Email:
Equal Opportunity Employer: 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.
Minimum Number of References Required: 2
Maximum Number of References Allowed: 4
Keywords: research, oral health, health policy, data, machine learning, AI
Supplemental Questions: Required fields are indicated with an asterisk (*).
PI