Senior Data Scientist, Trust (Inference)
New
J
JobgetherTrust and Safety
Fully remote role within eligible U.S. statesFull-TimeSenior
Salary$179,000 to $210,000 USD
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Job Details
- Experience
- Master's degree with at least 5 years of industry experience, or a PhD with 2+ years of relevant experience.
- Required Skills
- PythonSQLMachine LearningR
Requirements
- Master's degree in Statistics, Economics, Computer Science, Mathematics, or another quantitative discipline.
- At least 5 years of industry experience in data science or quantitative analysis (or a PhD with 2+ years of relevant experience).
- Deep expertise in experimentation design, causal inference methodologies, and statistical analysis.
- Strong experience with Bayesian modeling for uncertainty quantification, measurement, and decision support.
- Advanced programming skills in SQL and Python or R for data analysis and statistical modeling.
- Proven ability to lead complex analytical initiatives and influence cross-functional stakeholders in product or technology environments.
- Strong understanding of machine learning evaluation and translating analytical insights into business strategy.
- Excellent communication and storytelling skills with the ability to explain sophisticated statistical concepts to diverse audiences.
- Demonstrated ability to navigate ambiguity, prioritize high-impact opportunities, and deliver actionable insights in fast-paced environments.
Responsibilities
- Design and implement robust measurement frameworks to evaluate the effectiveness of trust and safety initiatives and identify opportunities for continuous improvement.
- Lead the design, execution, and analysis of experiments and quasi-experiments in complex environments where traditional A/B testing may not be feasible.
- Develop statistical, Bayesian, and causal inference models to assess risk, estimate treatment effects, and improve decision-making.
- Partner with product, engineering, operations, and policy teams to translate analytical findings into strategic recommendations and product enhancements.
- Produce leadership-ready analyses, visualizations, and presentations that communicate complex technical concepts to both technical and non-technical audiences.
- Evaluate the performance of machine learning systems by providing rigorous measurement methodologies and causal interpretations of model outputs.
- Drive the evolution of data science practices by identifying scalable approaches, improving methodologies, and contributing to long-term scientific strategy.
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