Data Scientist III

As a Data Scientist III , you will help build industry-leading solutions that empower GitHub’s Enterprise and Developer customers worldwide. The ideal candidate will leverage advanced data science and business acumen to address operational and product challenges, with a focus on support forecasting, capacity planning, product adoption, and product health. Drives the development and refinement of predictive models to forecast support ticket volume, workload trends and resource needs. Consider the impact of AI and automation in forecasting models. Aligns staffing and scheduling with demand, balances workloads across teams, and provides actionable insights to the business stakeholders to facilitate the right business decisions.

Responsibilities

• Identify and acquire data necessary for analysis, perform transformation and exploration, while adhering to GitHub’s privacy policies

• Build, maintain, and refine forecasting models for the business trends and business resource needs. Translate forecasts into actionable staffing and scheduling recommendations aligned with service-level goals.

• Deliver forward-looking insights to highlight risks and enable proactive action.

• Present findings and recommendations through visualizations, dashboards and PowerBI reports to support decision making for strategic and operational audiences.

• Collaborate with Support Leadership, Analytics, and cross-functional partners to align on forecasting assumptions, methodologies, and resource planning priorities and drive operational excellence through careful forecasting, proactive monitoring, and diagnostics.

• Collaborate closely with the engineering team to consider upcoming AI automations and their impact on support capacity needs

• Collaborate with others to perform data science experiments using established methodologies and statistics, identifying appropriate tools and techniques.

• Leverage broad and deep knowledge of modeling techniques for forecasting, and scaling workforce. Consider and account for risks of data leakage, bias/variance tradeoff, and methodological limitations.

• Write efficient, readable and extensible code that spans multiple features/solutions, adhering to software engineering concepts and practices.

• Build documentation for knowledge transfer and deployment of predictive analytic models.

Qualifications

Required Qualifications

• Bachelor’s Degree in Data Science, Mathematics, Physics, Statistics, Economics, Operations Research, Computer Science, or related field AND 4+ years experience in data science (e.g., managing structured and unstructured data, applying statistical techniques), forecasting, capacity planning, or workforce analytics or related field

  • OR Master’s Degree in Data Science, Mathematics, Physics, Statistics, Economics, Operations Research, Computer Science, or related field AND 2+ years experience in data science (e.g., managing structured and unstructured data, applying statistical techniques) or related field

  • OR Doctorate Degree in Data Science, Mathematics, Physics, Statistics, Economics, Operations Research, Computer Science, or related field

  • OR equivalent experience.

Preferred Qualifications

• Strong proficiency in data analysis and visualization tools (e.g., Power BI, SQL, Excel).

• Excellent problem-solving and communication skills, with the ability to influence stakeholders and present insights with clarity.

• Experience building forecasting models and translating outputs into actionable recommendations.

• Forecasting in support operations experience

• Experience in Python, MySQL or similar