Data Scientist

Role overview

Responsibilities

• check_circle Partner closely with product, business, and analytics stakeholders to deeply understand problem statements and translate them into actionable, data-driven solutions.
• check_circle Design, build, and deploy predictive and prescriptive models using classical statistical methods and machine learning.
• check_circle Lead fast-paced, agile experimentation, iterating quickly to demonstrate value and inform product development and releases.
• check_circle Apply design thinking principles to develop solutions that are scalable, usable, and aligned with business needs.
• check_circle Act as a technical expert in advanced modelling techniques, supporting solution design and peer reviews.
• check_circle Develop and evolve capabilities in Generative AI and Agentic AI, contributing to next-generation analytics solutions.
• check_circle Industrialise and scale solutions on cloud-based platforms, ensuring robustness, performance, and maintainability.
• check_circle Build end-to-end data science solutions addressing complex business problems through diagnostic, predictive, and prescriptive analytics.
• check_circle Unlock new insights by integrating internal and external data sources (e.g. retailer data, econometric models, panel data).
• check_circle Innovate new methodologies driven by local market needs, contributing to the global D&A product pipeline.
• check_circle Operate primarily as a strong individual contributor, working across multiple markets and teams in close partnership with business interpreters.
• check_circle Champion continuous improvement through:
• check_circle Simplified and standardised ways of working
• check_circle Improved development and delivery practices
• check_circle Degree qualified in a relevant technical discipline (Data Science, Computer Science, Engineering, Mathematics, Statistics, Econometrics, Operations Research, or similar).
• check_circle Strong track record of solving complex business problems using quantitative and statistical approaches.
• check_circle 3yrs or more experience in Deep expertise in several of the following with solid theoretical grounding:
• check_circle Regression and econometric modelling (Required)
• check_circle Time series forecasting (Required)
• check_circle Causal inference (Required)
• check_circle Simulation and optimisation (Required)
• check_circle Recommendation engines (Preferred)
• check_circle Churn modelling (Preferred)
• check_circle Experience developing and industrialising machine learning and advanced analytics solutions.
• check_circle Advanced proficiency in Python and Spark, with experience working in Databricks and Azure environments.
• check_circle Proven ability to work with large, complex, high-dimensional datasets, both structured and unstructured (e.g. SAP, POS data).
• check_circle Exposure to LLMs and agent-based systems is a plus.
• check_circle Excellent communication, active listening, and presentation skills, able to engage audiences at different levels of the organisation.
• check_circle Highly inquisitive and analytical mindset, with a passion for problem solving, simplification, and continuous improvement.
• check_circle Well-organised, with strong time management skills and the ability to prioritise effectively in a fast-paced, global environment.
• check_circle Proactive self-starter who thrives with autonomy while collaborating effectively within cross-functional and virtual teams.
• check_circle Passion for delivering excellence; and developing a culture of “easy to do business with”, where stakeholder’s needs are anticipated
• check_circle High ethical standards in data handling and decision-making.
• check_circle Attractive total remuneration package: excellent company pension, bonus, share scheme.
• check_circle Flexible cross-disciplinary career opportunities and a wealth of training opportunities & wellbeing resources whenever and wherever.
• check_circle Plenty of company-paid holidays to further ensure your work-life balance is maintained.
• check_circle We encourage an inclusive culture, which comes to life with interchangeable public holidays, paid paternity leave of 6 weeks and our transgender policy.
• check_circle Under the Hybrid Working principles, you will be expected to spend a minimum of 40%-60% in the office or at customers, suppliers or partners to connect and collaborate. For the time you work from home, we will ensure you are well equipped. When you are at the office, you can enjoy our tasty canteen with prepped food and own products.
• check_circle Informal culture and being the first one trying our new products.
• check_circle My Fitness Plan (reduction on your Fitness Subscription).
• check_circle Homework allowance
• check_circle Company laptop and mobile phone
• check_circle Green Mobility Policy.

About the company