Position Purpose:

We are transforming how merchandising decisions are made through AI-powered solutions and automation. This Sr. Data Scientist plays a key role to build scalable, mathematical algorithms in production that directly impact retail and merchandising by solving complex, high-value business problems. The position focuses on science-driven models, operating at the intersection of data science, process automation, cloud deployment, and software production to deliver reliable decision systems that increase efficiency and improve customer experience.

This role leads Machine Learning initiatives end-to-end, from cross-functional collaboration and business problem framing through technical design, development, deployment, and ongoing monitoring and enhancement. The Sr. Data Scientist partners closely with product managers, software engineers, and business stakeholders to identify high-impact opportunities, translate into technical requirements, and deliver scalable solutions in production. The role is responsible for communicating insights and recommendations to both technical and non-technical audiences, mentoring data scientists on projects, and ensuring models perform effectively based on real-world outcomes.

Key Responsibilities:

35% Solution Development - Proficiently design and develop algorithms and models to use against large datasets to create business insights; Execute tasks with high levels of efficiency and quality; Make appropriate selection, utilization and interpretation of advanced analytical methodologies; Effectively communicate insights and recommendations to both technical and non-technical leaders and business customers/partners; Prepare reports, updates and/or presentations related to progress made on a project or solution; Clearly communicate impacts of recommendations to drive alignment and appropriate implementation30% Project Management & Team Support - Work with project teams and business partners to determine project goals; Provide direction on prioritization of work and ensure quality of work; Provide mentoring and coaching to more junior roles to support their technical competencies; Collaborate with managers and team in the distribution of workload and resources; Support recruiting and hiring efforts for the team20% Business Collaboration - Leverage extensive business knowledge into solution approach; Effectively develop trust and collaboration with internal customers and cross-functional teams; Provide general education on advanced analytics to technical and non-technical business partners; Deep understanding of IT needs for the team to be successful in tackling business problems; Actively seek out new business opportunities to leverage data science as a competitive advantage15% Technical Exploration & Development - Seek further knowledge on key developments within data science, technical skill sets, and additional data sources; Participate in the continuous improvement of data science and analytics by developing replicable solutions (for example, codified data products, project documentation, process flowcharts) to ensure solutions are leveraged for future projects; Define best practices and develop clear vision for data analysis and model productionalization; Contribute to library of reusable algorithms for future use, ensuring developed codes are documented

Direct Manager/Direct Reports:

This position reports to manager or aboveThis position has 0 Direct Reports

Travel Requirements:

Typically requires overnight travel less than 10% of the time.

Physical Requirements:

Most of the time is spent sitting in a comfortable position and there is frequent opportunity to move about. On rare occasions there may be a need to move or lift light articles.

Working Conditions:

Located in a comfortable indoor area. Any unpleasant conditions would be infrequent and not objectionable.

Minimum Qualifications:

Must be eighteen years of age or older.Must be legally permitted to work in the United States.

Preferred Qualifications:

Master’s or PhD in Data Science, Statistics, Economics, Applied Math, Engineering, or other quantitative and engineering fields.6+ years of hands-on experience developing and deploying Machine Learning models into production environments and integrating into scalable data pipelines and decision systems (e.g., via APIs, microservices, or batch pipelines), ensuring reliability, scalability, traceability, and interoperability.Deep expertise in causal inference (e.g., Difference-in-Differences, Double ML, Synthetic Control) and discrete choice models, including elasticity, substitution and demand transfer.Solid foundation in machine learning models (e.g., regularized regression, tree-based methods such as XGBoost, and neural networks)Strong experience with forecasting models (e.g., time-series forecasting. ARIMA, Bayesian and probabilistic methods or deep learning-based approaches).Strong understanding of data structures, and modern cloud ecosystems (GCP, AWS, etc.).Proficient with data visualization software (preferably Tableau).Familiarity with GenAI, LLM and Agentic framework, with experience integrating LLM-based reasoning into ML-driven solutions.Comfortable collaborating with front-end developers or building light UI prototypes (e.g., Streamlit, React).Demonstrated strength in business communication and technical leadership, with the ability to clearly explain complex statistical and ML concepts to non-technical stakeholders in a way that builds trust and drives adoption.Experience solving retail or merchandising problems such as assortment & space optimization, demand transfer, consumer choice models, demand forecasting.

Minimum Education:

The knowledge, skills and abilities typically acquired through the completion of a bachelor's degree program or equivalent degree in a field of study related to the job.

Preferred Education:

No additional education

Minimum Years of Work Experience:

5

Preferred Years of Work Experience:

No additional years of experience

Minimum Leadership Experience:

None

Preferred Leadership Experience:

None

Certifications:

None

Competencies:

Attracts Top Talent: Attracting and selecting the best talent to meet current and future business needsBusiness Insight: Applying knowledge of the business and the marketplace to advance the organization's goalsCollaborates: Building partnerships and working collaboratively with others to meet shared objectivesCommunicates Effectively: Developing and delivering multi-mode communications that convey a clear understanding of the unique needs of different audiencesCultivates Innovation: Creating new and better ways for the organization to be successfulCustomer Focus: Building strong customer relationships and delivering customer-centric solutionsDevelops Talent: Developing people to meet both their career goals and the organization's goalsDirects Work: Provides direction, delegating and removing obstacles to get work doneDrives Results: Consistently achieving results, even under tough circumstancesNimble Learning: Actively learning through experimentation when tackling new problems, using both successes and failures as learning fodderOptimizes Work Processes: Knowing the most efficient and effective processes to get things done, with a focus on continuous improvementSelf-Development: Actively seeking new ways to grow and be challenged using both formal and informal development channels