Why This Role Stands Out
Leverage your expertise to drive impactful decisions in retail and merchandising as a Lead/Senior Data Scientist, with the flexibility of a remote role. If you excel at transforming complex data into actionable insights and enjoy guiding a team, this is a fantastic opportunity to shape strategy and advance your career. Apply now to make a significant contribution!
Quick Overview
Job Description
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.
- 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.
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