Data Scientist, Merchandising Analytics

Tractor Supply Company•Brentwood, TN

3d•Hybrid

About The Position

The Data Scientist, Merchandising Analytics at Tractor Supply Company will play a key role in leveraging data to address complex business challenges. The role will develop advanced statistical methods using Machine Learning, AI, statistical modeling, and optimization techniques to support the merchandising strategies and broader organizational goals of TSC. Additionally, the role will contribute to setting objectives to enhance the overall data architecture and data governance within the Merchandising team. Key areas of focus within Merchandising will be Space Planning and Pricing. The Data Scientist will lead cross-functional projects, design and implement predictive models, and promote data-driven decision-making throughout the organization. Strong communication skills are essential as this role will translate complex analytical results into clear, actionable insights for both technical and non-technical stakeholders. This role work will ensure that Tractor Supply Company remains at the forefront of industry trends and emerging technologies in the data science field.

Requirements

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.
Bachelor’s Degree in Mathematics, Statistics, or Econometrics.
Any combination of education and experience will be considered.

Nice To Haves

Intermediate-advanced in one or more programming language (Python, PySpark, R).
Deep expertise in writing and debugging complex SQL queries.
Ability to frame business questions and create an analytics solution 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.
Must possess high degree of aptitude in communicating both verbally and written 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.

Responsibilities

Work closely with key business partners to fully explore and frame a business question including objectives, goals, KPIs, decisions the analysis will support and required timing for deliverables.
Extracting 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 our 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 proven, predictive science to right-size every store with localized plans that balance individual store space allocations with your top-down and bottom-up strategies.
Be 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.