Sr Data Scientist, Merchandising Analytics

Overall Job Summary

The Senior Data Scientist will be responsible for modeling complex business problems and initiating the development of advanced statistical methods through Machine Learning/ AI, statistical modeling, and optimization to support the broader Merchandising organization and TSC. In addition to statistical modeling, this position will be tasked with setting goals to drive the overall data architecture and data governance for Merchandising.

This position will lead cross-functional projects, designing and implementing predictive models, and driving overall effective data-driven decision-making. Strong communication skills are required to effectively convey findings to both technical and non-technical stakeholders. This position will own the translation of predictive modeling results to actionable insights that can be utilized across the TSC organization, ensuring the company stays abreast of industry trends and emerging technologies in the Data Science field.

Essential Duties and Responsibilities (Min 5%)

Data Science & Advanced Analytics:

• Develop, maintain, and improve predictive models using Python, R, and Databricks to enhance business insights.
• Extract and transform data from internal and external sources to build robust data science solutions that support key business decisions.
• Design and implement A/B testing frameworks to evaluate the effectiveness of various business strategies, ensuring statistical rigor in experiment design and analysis.
• Stay at the forefront of the AI and Machine Learning ecosystem, continuously evaluating and implementing emerging technologies to drive innovation.

Business & Strategic Collaboration:

• Work closely with key business stakeholders to frame complex business questions, define objectives, KPIs, and deliverables, and ensure alignment of analytical solutions with strategic goals.
• Translate predictive modeling outputs into actionable insights that drive tangible business impact across merchandising, pricing, and operational functions.
• Foster a data-driven decision-making culture, collaborating with cross-functional teams and senior leadership to define the long-term vision for data science and engineering within the organization.

Data Engineering & Automation:

• Identify opportunities for automation and optimization within data pipelines, modeling workflows, and analytics processes.
• Work closely with data engineering and...

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