Note: The job is a remote job and is open to candidates in USA. GitHub is a leading AI-powered developer platform used by developers and organizations worldwide. The Senior Data Scientist will lead data acquisition and quality efforts, develop and evaluate data science and machine learning models, and generate insights to support business decisions. The role also involves mentoring others, communicating complex findings, and driving reliable model deployment and data-driven strategies.
Responsibilities
- Lead data acquisition efforts and ensure data is properly formatted and accurately described, while adhering to GitHub's privacy policies
- Mentor others in data cleaning and data analysis best practices. Identify gaps in current data sets and drive onboarding of new data sets from production systems or third-party vendors
- Resolve data integrity problems in collaboration with relevant teams to promote upstream change and long-term quality
- Leverage broad and deep knowledge of data modeling techniques, AI/ML tools, programming languages and query languages to create models, conduct experiments, analyze results, evaluating the methodology and performance of team members' models and recommending improvements
- Drive best practices relative to model validation, implementation, and application, and partners with teams across the organization to identify and explore new opportunities for driving transformative solutions for our stakeholders and customers
- Develop and articulate data-driven strategies in consideration of business priorities and lead conversations with end customers and/or internal stakeholders to understand, define, and solve business problems
- Communicate complex statistics, and machine learning topics to diverse audiences (e.g., multidisciplinary teams, customers, technical and non-technical audiences)
- Independently writes efficient, readable, extensible code that spans multiple features/solutions. Contributes to the code/model review process by providing feedback and suggestions for implementation and improvement
- Drive operational excellence for model deployment (i.e. performance, scalability, monitoring, maintenance, integration into engineering production system, stability)
- Produce project plans to define necessary steps required for completion, leading to a measurable improvement in business performance metrics over time
Skills
- Bachelor's Degree in Data Science, Mathematics, Physics, Statistics, Economics, Operations Research, Computer Science, or related field AND 5+ years experience in data science (e.g., managing structured and unstructured data, applying statistical techniques) or related field
- OR Master's Degree in Data Science, Mathematics, Physics, Statistics, Economics, Operations Research, Computer Science, or related field AND 3+ years experience in data science (e.g., managing structured and unstructured data, applying statistical techniques) or related field
- OR Doctorate in Data Science, Mathematics, Physics, Statistics, Economics, Operations Research, Computer Science, or related field AND 1+ year(s) experience in data science (e.g., managing structured and unstructured data, applying statistical techniques) or related field
- OR equivalent experience
- Technical understanding of data science techniques for regression, classification, time-series analysis, experimental design, causal inference
- Proficiency in programming languages such as Python or R, experience with query languages such as SQL and KQL, and with data manipulation tools like Spark and Airflow
- Able to clearly communicate findings to non-technical stakeholders through storytelling and visualization with tools like Jupyter notebooks or Azure Data Explorer/ PowerBI dashboards
Benefits
- Annual bonus for certain roles
- Stock for certain roles
- Sales incentives based on revenue or utilization for certain roles, depending on the terms of the plan and the employee's role
- Remote-first work arrangement
- Learning and growth opportunities
- Excellent benefits to support employees
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