Lead / Senior Data Scientist (Retail & Merchandising)

Prohires; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Prohires is seeking a Lead / Senior Data Scientist with strong retail domain experience to transform sales, pricing, promotions, and assortment data into actionable insights for Walmart. This is a hands-on role that also involves leading a small team.

You will work across merchandising, pricing, and commercial teams, build and deploy models for demand forecasting and pricing, and mentor junior data scientists while presenting recommendations to senior stakeholders.

Qualifications

• 7+ years in data science or advanced analytics, with ≥4 years in retail/ecommerce/merchandising.
• Hands-on experience with retail sales, merchandising and assortment data.
• Proven work in pricing, promotions, demand forecasting, or product performance.
• Strong Python (or R) and SQL skills for large-scale data.
• Solid ML, time-series forecasting, statistics and experimentation.
• Experience translating business problems into deployable models.
• Leadership experience mentoring data science staff.

Responsibilities

• Define business problems with merchandising and pricing teams and translate to data science solutions.
• Mine and analyze large datasets to identify drivers of sales, margin and customer behavior.
• Build and deploy ML, forecasting and predictive models for demand, pricing and promotions.
• Use retail data to support range planning, inventory and category decisions.
• Analyze customer behavior via segmentation and propensity modeling.
• Measure pricing/promotions impact with A/B tests and causal methods.
• Remain hands-on technically while setting direction and mentoring juniors.
• Present findings and recommendations to senior stakeholders and track impact.

Skills

Retail analytics

Python

SQL

Machine learning

Time-series

Experimentation

Team leadership

Business translation

Education

Bachelor's or Master's in a related field

Tools

Spark / Databricks

AWS

Power BI

Job description

Job Title: Lead / Senior Data Scientist (Retail & Merchandising)

Location: Remote

Duration: Full Time

Client: Walmart

Role overview

We are looking for a Lead / Senior Data Scientist with strong retail domain experience to turn sales, merchandising and customer data into better decisions on pricing, promotions, assortment and demand. This is a hands-on technical role that also involves leading the data science work and guiding a small team.

Key responsibilities

• Work with merchandising, category, pricing and commercial teams to define business problems and turn them into data science solutions.
• Mine and analyse large customer, product and transaction datasets to find what drives sales, margin and customer behaviour.
• Build and deploy machine learning, forecasting and predictive models for demand forecasting, pricing, promotion effectiveness and product performance.
• Use retail sales, merchandising and assortment / category management data to support range planning, inventory and category decisions.
• Analyse customer behaviour through segmentation, basket analysis, propensity modelling and lifetime value.
• Measure the impact of pricing and promotional changes using A/B tests, test-and-learn and causal methods.
• Stay hands-on in code and modelling while setting technical direction, reviewing work and mentoring junior data scientists and analysts.
• Present findings and recommendations clearly to senior business stakeholders and track business impact.

Required qualifications

• 7 years in data science or advanced analytics, with at least 4 years in retail, e-commerce, FMCG/CPG or merchandising.
• Hands-on experience with retail sales, merchandising and assortment / category management data.
• Proven work in at least one of: pricing, promotions, demand forecasting, customer behaviour or product performance.
• Strong skills in Python (or R) and SQL, with experience handling large-scale transactional data.
• Solid grounding in machine learning, time-series forecasting, statistics and experimentation.
• Track record of translating business and merchandising problems into models that were actually used.
• Experience leading projects and guiding or mentoring other data scientists.
• Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Economics, Operations Research or a related field.

Preferred qualifications

• Experience with price elasticity, markdown optimisation, promotion uplift or assortment optimisation models.
• Familiarity with cloud data platforms (AWS, Azure or Google Cloud Platform), Spark / Databricks, and MLOps tools.
• Exposure to BI tools such as Power BI or Tableau for stakeholder reporting.
• Experience working in a client-facing or consulting environment.

What we're looking for

Someone strong enough technically to build models themselves, and senior enough to lead the work and guide a team. Real retail / merchandising experience matters most: we will prioritise it over a strong generic data scientist without retail exposure.