Senior Data Scientist, Research, Real World Journeys
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Minimum qualifications:
- Master's degree in Statistics, Data Science, Mathematics, Physics,
Economics, Operations Research, Engineering, or a related quantitative
field. - 5 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of work experience with a PhD degree.
Preferred qualifications:
- 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree.
- 2 years of experience in GenAI, Large Language Models (LLM’s), and Supervised Machine Learning.
- Ability to think critically, analyze complex problems, and develop data-driven solutions with a strategic mindset.
- Track record of using data science to solve unstructured business problems and translate the results into impactful business and product recommendations.
About the job
The (RWJ) Real World Journeys team’s mission is to inspire action by connecting people with experiences that make life better. RWJ supports a range of user journeys such as Food and Drink, Services, Lodging, Flights, and Things to Do. In this role, you will work cross-functionally with multiple leads from Engineering and Product to uncover new product opportunities and shape strategic directions. You will have the opportunity to apply advanced modeling techniques (LLM, causal inference, machine learning) to solve complex business problems.
The US base salary range for this full-time position is $166,000-$244,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Responsibilities
- Collaborate with stakeholders in cross-projects and team settings to identify and clarify business or product questions to answer. Provide feedback to translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models.
- Use custom data infrastructure or existing data models as appropriate, using specialized knowledge. Design and evaluate models to mathematically express and solve defined problems with limited precedent.
- Gather information, business goals, priorities, and organizational context around the questions to answer, as well as the existing and upcoming data infrastructure.
- Own the process of gathering, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python). Apply analytics, experimentation, causal inference and LLM to address business issues.
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