Senior Data Scientist

GitHub is seeking experienced professionals to elevate our data and analytics efforts. As a Senior Data Scientist in Data Science, you will leverage your deep expertise and knowledge of data science, AI/ML, analytics engineering, and business to lead data acquisition efforts, conduct thorough review of data analysis and data quality, form hypotheses and discover insights in the data to support business stakeholders and their decision making. The ideal candidate will contribute to the impact of our Data Science initiatives and gain deep insights into the latest advancements in AI, machine learning and data science.

• 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.

• 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)

in data science (e.g., managing structured and unstructured data, applying statistical techniques) or related field OR equivalent experience

• 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)

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

GitHub values

• Customer-obsessed
• Ship to learn
• Growth mindset
• Own the outcome
• Better together
• Diverse and inclusive

Manager fundamentals

• Model
• Coach
• Care

Leadership principles

• Create clarity
• Generate energy
• Deliver success