Remote - Data Scientist

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

Location: Remote

Duration: Full Time

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.