Sr. Data Scientist - AI Research
New
J
JobgetherAI Research
The position is fully remote within the United StatesFull-TimeSenior
SalaryAnnual base salary range of $128,000–$197,000
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Job Details
- Experience
- 5+ years of professional data analysis or data science experience
- Required Skills
- PythonSQLData AnalysisMachine LearningPrompt EngineeringGenerative AI
Requirements
- 5+ years of professional data analysis or data science experience in an industry environment, preferably with product analytics or AI/ML-related work.
- Demonstrated experience partnering closely with product and engineering teams to translate analytical findings into practical solutions.
- Strong cross-functional collaboration skills, with the ability to work effectively across technical, business, and ideally clinical domains.
- Strong understanding of statistical concepts and methods, including experimentation, probability, regression, and hypothesis testing.
- Experience conducting comprehensive analyses using irregular, complex, or disparate datasets.
- Advanced SQL proficiency, including the ability to write complex queries across multiple schemas and tables.
- Graduate-level statistics coursework and/or an MS in a quantitative discipline such as statistics, econometrics, biostatistics, or quantitative social sciences is preferred.
- Experience with Python for data cleaning, analysis, JSON parsing, API integration, user-defined functions, and automation is preferred.
- Familiarity with AI/ML research and development, including prompt engineering and RAG, is a strong plus.
- Interest or experience in public health is advantageous.
- Strong ownership, curiosity, problem-solving ability, and comfort working independently in a fast-moving, collaborative environment.
Responsibilities
- Partner with Data, Product, Engineering, and other cross-functional teams to develop AI/ML solutions that improve platform experiences for providers, clients, and users.
- Develop deep expertise in diverse data sources and collaborate with data engineering teams to create reliable pipelines that incorporate appropriate clinical and business logic.
- Analyze complex and irregular datasets from multiple sources, identifying patterns and translating findings into actionable product and business insights.
- Develop predictive and generative models and establish rigorous evaluation frameworks to measure their effectiveness and guide product iterations.
- Apply statistical methodologies, experimentation, and hypothesis testing to answer complex business and product questions.
- Support AI/ML research and development initiatives, including emerging applications such as prompt engineering and retrieval-augmented generation (RAG).
- Handle time-sensitive ad hoc analytical requests from internal and external stakeholders with accuracy and responsiveness.
- Communicate analytical findings, methodologies, and recommendations clearly to technical, business, and, where applicable, clinical audiences.
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