Staff Data Scientist

About the role

The Staff Data Scientist will build models, experiments, and AI systems that inform pricing decisions for Global Partners' fuel and convenience store business. They will own the modeling approach, evaluate models for production readiness, and advance pricing from forecasting to automated recommendations.

Responsibilities

• Own demand and price response modeling end to end, from problem framing through production.
• Deliver probabilistic forecasts at daily and intraday resolution for pricing and planning use.
• Compare candidate modeling approaches against strong baselines and select on evidence.
• Define model evaluation and the criteria for promoting a model into production.
• Advance pricing from forecasting toward automated price recommendation, with appropriate safeguards.
• Design and analyze pricing field experiments, including power analysis and site selection.
• Build and deploy agentic and large language model automation for analytical workflows.
• Define how AI and agentic systems are evaluated, including harnesses, benchmarks, and reusable skills.
• Set orchestration standards for scheduled model and agent workloads.
• Establish observability for models and agents in production, covering data quality, drift, cost, and alerting.
• Serve as technical design reviewer for pricing programs delivered by other teams.
• Partner with machine learning engineering to deploy, version, and monitor production models.
• Mentor data scientists and present technical work to leadership and business stakeholders.

Requirements

• Bachelor's degree in Computer Science, Statistics, Mathematics, Physics, or related quantitative field required; PhD/Master's degree in Machine Learning, AI, or related discipline preferred.
• 7+ years of industry data science or machine learning experience, including ownership of production models.
• Deep expertise in demand forecasting and price response modeling, including probabilistic output and calibration.
• Experience designing and analyzing field experiments, including power analysis and randomization.
• Reinforcement learning experience a bonus.
• Experience building and deploying agentic and large language model automation.
• Experience evaluating AI systems using harnesses and benchmarks.
• Expert level Python and SQL, with Git, code review, automated testing, and continuous integration.
• Experience with a cloud machine learning platform, AWS SageMaker preferred, including model registry, monitoring, and alerting.
• Experience with a cloud data warehouse, Snowflake preferred, and with transformation and orchestration tooling such as dbt and Dagster.
• Experience delivering results through BI and application tooling such as Tableau and Streamlit.
• Experience raising technical quality through specification, design review, and mentoring.
• Strong written and verbal communication with both technical and business audiences.
• Domain experience in fuel, retail, or another pricing intensive industry preferred.

Qualifications

• Bachelor's degree in Computer Science, Statistics, Mathematics, Physics, or related quantitative field required; PhD/Master's degree in Machine Learning, AI, or related discipline preferred.
• 7+ years of industry data science or machine learning experience, including ownership of production models.
• Deep expertise in demand forecasting and price response modeling, including probabilistic output and calibration.
• Experience designing and analyzing field experiments, including power analysis and randomization.
• Reinforcement learning experience a bonus.
• Experience building and deploying agentic and large language model automation.
• Experience evaluating AI systems using harnesses and benchmarks.
• Expert level Python and SQL, with Git, code review, automated testing, and continuous integration.
• Experience with a cloud machine learning platform, AWS SageMaker preferred, including model registry, monitoring, and alerting.
• Experience with a cloud data warehouse, Snowflake preferred, and with transformation and orchestration tooling such as dbt and Dagster.
• Experience delivering results through BI and application tooling such as Tableau and Streamlit.
• Experience raising technical quality through specification, design review, and mentoring.
• Strong written and verbal communication with both technical and business audiences.
• Domain experience in fuel, retail, or another pricing intensive industry preferred.

Skills

• Expert level Python and SQL.
• Git, code review, automated testing, and continuous integration.
• AWS SageMaker, model registry, monitoring, and alerting.
• Snowflake, cloud data warehouse.
• dbt, Dagster, transformation and orchestration tooling.
• Tableau, Streamlit, BI and application tooling.
• Reinforcement learning experience a bonus.

Benefits

Health & Wellness - Medical, Dental, Visions and Life Insurance. Additional wellness support.

The Road Ahead – 401k and a match component. Tuition reimbursement.

Pay

$160,500.00 - $240,800.00