Data Scientist III

About the role

The Data Scientist III specializes in Generative AI and agentic architectures, driving internal data analytics projects ranging from short explorations to long-term predictive and machine learning model implementations. They seek out new data sources and apply analytical methods to solve business problems, communicate findings to all organizational levels, and influence strategic decisions through data-driven recommendations.

Responsibilities

• Builds robust Agentic AI and RAG applications using Responsible AI practices across model development, deployment, and governance.
• Performs time-series analyses, hypothesis testing, and causal analyses to statistically assess relative impact and extract trends across all relevant functional areas.
• Resolves data inquiries and requests, providing insights and serving as a subject matter expert for department data.
• Documents requirements for data science and reporting projects, supports the development of standard data analyses, reports, and dashboards, and collaborates with other teams to gather data and build relationships.
• Designs experiments and interprets results to draw detailed and actionable conclusions, builds statistical models to enhance understanding of trends and predict future performance, and finds new opportunities and novel applications for core internal data.
• Translates and champions Machine Learning and advanced analytics capabilities for non-technical audiences, participates in end-to-end data science project lifecycle, designs, validates, and evaluates solutions using Python, SQL, and other programming tools, educates and mentors team members on best practices for data analytics, and performs other job-related duties as assigned or apparent.

Qualifications

• Master’s degree preferred, Bachelor’s Degree in an analytical field preferred.
• 5 years of demonstrated experience working with large databases to perform complex analysis.
• 5 years of demonstrated experience with statistics and multivariate analytical techniques including multivariate regression, logistic regression, cluster analysis, design of experiments, machine learning, and decision trees.
• Demonstrated expertise building and deploying machine learning/AI models in a cloud computing environment (e.g., AWS) and/or enterprise IT environment.
• Demonstrated expertise with common commercial analytics topics (e.g., pricing optimization, customer segmentation, customer churn/lifetime value, etc.) or operational analytics topics (e.g., logistics analytics, route optimization, maintenance optimization, etc.).

Skills

• Proficiency with programming in Python in data science and/or statistical analytics settings.
• Proficiency with relational databases and the ability to write SQL queries.
• Proficiency with Excel and PowerBI.
• Proficiency with cloud computing environments (e.g., AWS).
• Proficiency with Snowflake.

Benefits

• Comprehensive medical benefits coverage, dental plans and vision coverage.
• Health care and dependent care spending accounts.
• Short- and long-term disability.
• Life insurance and accidental death & dismemberment insurance.
• Employee and Family Assistance Program (EAP).
• Employee discount programs.
• Retail retirement plan with a generous company match.
• Employee Stock Purchase Plan (ESPP).
• Paid Time Off (PTO).