Senior Data Scientist
United StatesFull-TimeSenior
Salary120,000 - 175,000 USD per year
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLMachine Learning
Requirements
- 5+ years of experience in data science, applied statistics, or machine learning roles
- Strong expertise in predictive modeling, experiment design, and causal inference
- Advanced proficiency in SQL and Python for large-scale, complex datasets
- Experience working with modern data stacks, including cloud data warehouses and transformation tools
- Proven ability to build, deploy, and maintain production-grade ML models
- Strong analytical thinking with the ability to distinguish signal from noise in complex datasets
- Excellent communication skills, including the ability to explain technical concepts to non-technical stakeholders
- Experience working in ambiguous, fast-evolving environments with high ownership expectations
- Familiarity with AI-assisted workflows and LLM-based tools is a plus
Responsibilities
- Lead end-to-end data science initiatives that transform ambiguous business questions into structured analytical and machine learning solutions, delivering predictive insights that support strategic and operational decision-making across the organization
- Own the full lifecycle of data science projects, from problem framing and data exploration to modeling, deployment, and monitoring
- Build and productionize machine learning models in collaboration with data engineering teams
- Apply statistical modeling, causal inference, and experimentation techniques to generate actionable business insights
- Evaluate model performance and communicate trade-offs, limitations, and implications for business decisions
- Conduct deep-dive analyses on large-scale, multi-source datasets to identify trends and opportunities
- Translate complex analytical findings into clear, impactful recommendations for executive and cross-functional stakeholders
- Contribute to the development of data science best practices, standards, and internal methodologies
- Partner with engineering and governance teams to improve data quality, structure, and usability
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