Data Scientist, Merchandising Analytics

About the role

The Data Scientist, Merchandising Analytics will leverage data to address complex business challenges, developing advanced statistical methods using Machine Learning, AI, statistical modeling, and optimization techniques to support merchandising strategies and broader organizational goals. Key areas of focus include Space Planning and Pricing. This role will lead cross-functional projects, design and implement predictive models, and promote data-driven decision-making throughout the organization, translating complex analytical results into clear, actionable insights for both technical and non-technical stakeholders.

Responsibilities

• Work closely with key business partners to fully explore and frame business questions including objectives, goals, KPIs, decisions the analysis will support, and required timing for deliverables.
• Extract available and relevant data from internal and external data sources to perform data science solution development.
• Develop, maintain, and improve predictive models using R, Python, and Databricks to enhance business knowledge and processes.
• Contribute and assist the team with best practices in data governance, data engineering, and data architecture.
• Identify opportunities for automation and continuous improvement within data pipelines, processes, and systems.
• Maintain a broad exposure to the wider ecosystem of AI / Machine Learning and ensure the team is pushing toward the most optimal solutions.
• Manage multiple projects simultaneously with limited oversight including development of new technologies and maintenance of existing framework.
• Foster a culture of data-driven decision making and collaborate with cross-functional teams and senior leadership to define the long-term vision and goals for data science and engineering within the organization.
• Design and execute A/B tests to evaluate the effectiveness of various data-driven solutions, including designing appropriate sample sizes, metrics for evaluation, and statistical analysis plans.
• Use predictive science to right-size every store with localized plans that balance individual store space allocations with top-down and bottom-up strategies.
• Serve as a 'Go-To' person for any data analytical needs ranging from data extraction/manipulations, long term trend analysis, statistical analysis, and modeling techniques.
• Perform code-review and debug with the team and assist during implementation where necessary.

Qualifications

• Bachelor's Degree in Mathematics, Statistics, or Econometrics (Master's Degree preferred). Any combination of education and experience will be considered.
• 3-5 years proven experience as a Data Scientist, preferably in the retail or e-commerce industry.
• Prefer 2+ years of experience in predictive modeling utilizing CRM or transaction information.

Skills

• Intermediate-advanced proficiency in one or more programming languages (Python, PySpark, R).
• Deep expertise in writing and debugging complex SQL queries.
• Ability to frame business questions and create analytics solutions using statistical or other advanced analytics methodologies.
• Proven advanced modeling experience in leading data-driven projects from definition to execution, driving and influencing project roadmaps.
• Experience using Azure, AWS, or another cloud compute platform (a plus).
• Familiarity with visualization tools such as Power BI and Tableau.
• High degree of aptitude in communicating both verbally and in writing complex analysis results to Senior & Executive Leadership.
• Knowledge of A/B testing methods; capable of designing a controlled test design, running the test, and providing measurement post-hoc.
• Proficiency with managing data repository and version control systems like Git.
• Speak, read, and write effectively in the English language.

Working Conditions

Hybrid / Flexible working conditions. Physical requirements include sitting, standing (not walking), walking, kneeling/stooping/bending, and lifting up to 10 pounds.