Job Opportunities API

The Data Scientist is responsible for developing predictive models, optimisation and analytical solutions across a broad range of business problems including demand forecasting, price and elasticity modelling, customer and store segmentation, and AI/LLM-based solutions that enable data-driven decisions across commercial and operational functions. This role bridges business needs and advanced analytics, combining strong statistical, machine-learning, and data engineering skills with the ability to source diverse data, translate complex results into clear insights, and deliver production-ready solutions. The successful candidate will be adept at understanding business requirements, building models end-to-end, telling compelling data stories, and delivering high-impact solutions on time. Responsibilities Modelling & Optimisation Design, develop, and deploy predictive and machine-learning models across areas such as demand forecasting, price and elasticity modelling, price/assortment optimisation, and recommendation Build customer and store segmentation, clustering, and entity-matching / item-mapping solutions to support commercial and marketing decisions Frame business problems as data science problems, selecting appropriate methods and validation approaches to deliver reliable, production-ready outcomes Continuously evaluate and improve model performance, accuracy, and business impact over time AI & Advanced Analytics Apply NLP and LLM/Generative AI techniques to use cases such as text classification, sentiment/voice-of-customer analysis, data mapping, and RAG or text-to-SQL applications Prototype and evaluate emerging AI approaches, turning promising experiments into practical business solution. Data, Insights & Data Sourcing Source, acquire, and integrate data from internal systems, third-party providers, and external sources (e.g. web scraping, APIs, public datasets) Explore, clean, and transform large datasets to prepare high-quality features; ensure data quality, consistency, and integrity Identify trends, patterns, and opportunities in data — including external factors — and proactively surface insights that drive business value Delivery & Productionisation Build and maintain data pipelines and scheduled jobs (e.g. on Databricks) to run models and analytics reliably in production Deliver results through dashboards, reports, and applications, and maintain clear documentation of models, data, and methodologies Business Partnering Engage with business stakeholders to understand objectives, gather requirements, and translate them into data science solutions Communicate complex results clearly to technical and non-technical audiences, and manage timelines and deliverables to agreed success criteria Requirements Bachelor's degree (minimum); Master's degree preferred in Statistics, Mathematics, Computer Science, Data Science, Engineering, or a related quantitative field Minimum 3–5 years of hands-on data science experience in a commercial or enterprise environment Experience in retail, FMCG, or e-commerce is a strong advantage Strong programming skills in Python and SQL with solid command of data science libraries ( e.g. pandas, scikit-learn, TensorFlow/PyTorch) Sound understanding of machine-learning and statistical techniques, with experience across several of: forecasting, elasticity/optimisation, segmentation/clustering, and entity matching Experience with NLP and LLM/Generative AI (e.g. embeddings, RAG, text-to-SQL) is a strong advantage Ability to source and integrate external data via web scraping and APIs (e.g. requests, Playwright/Selenium) Experience building and scheduling data pipelines, ideally on Databricks/Spark, or a similar big-data or cloud platform (Azure, AWS, or GCP) Strong data storytelling and visualisation skills; able to communicate insights clearly to technical and non-technical audiences Proven track record