Graduate Data Scientist
# Graduate Data Scientist **TECSA** · London W2 6LG · `On-site` 🕒 **Статус:** *Опубликовано: сегодня* · *Источник: Indeed* --- ### About the Role Tecsa is a leading specialist consultancy with a dual focus on loyalty programmes and software to support retail insights and retail media. We support major retailers and other consumer-facing businesses around the world, providing applications, analytics and AI agents to improve business performance. Tecsa is growing its data science consulting team and is seeking a Graduate Data Scientist to join us. This is a hands-on role combining data science, software development and analytical consulting, with the opportunity to work directly on both client projects and Tecsa's own technology products. You will work alongside experienced data scientists and consultants, developing your technical and commercial skills while contributing to real-world applications of data science and AI. Your responsibilities will include: Developing new analytical methodologies to derive insight from large and complex retail datasets Applying statistics and machine learning to understand consumer behaviour and business performance Designing, coding and testing new features within Tecsa's AudienceViu retail media targeting platform Creating and optimising AI agents within AudienceViu and OneViu Using Python, SQL and modern data platforms to build robust analytical solutions Undertaking ad-hoc analytical consulting to answer client questions and support decision-making Communicating analytical findings clearly to both technical and non-technical audiences This is an opportunity to begin your data science career in a varied environment where you can work across analytics, AI, software and consulting rather than being limited to a single area. You will have the opportunity to take ownership early, learn from experienced colleagues and see your work applied to live client and product challenges. Sponsorship is not available for this role. Candidates will need to have the right to work in the UK. Requirements Degree in a quantitative discipline such as Data Science, Computer Science, Mathematics, Statistics, Engineering, Physics, Economics or another relevant STEM subject Strong foundation in data science, including statistics and machine learning Good Python and SQL skills Understanding of core software engineering principles and databases Familiarity with modern AI tools and agentic coding practices Strong analytical and creative problem-solving skills Ability to communicate clearly and work effectively as part of a team Curiosity, initiative and a willingness to learn new technologies and approaches Desirable MSc or other postgraduate qualification in Data Science, Computer Science, Statistics, Mathematics or another relevant quantitative field Experience applying data science through an internship, placement, university project, research project or other practical work Familiarity with cloud data platforms and technologies such as Microsoft Fabric, Azure, AWS, GCP or Snowflake Some understanding of software development practices such as version control, testing and collaborative development Commercial awareness, particularly relating to retail operations, business finance, digital marketing, loyalty or consumer behaviour Basic understanding of UX and how users interact with analytical or software products Experience using generative AI, coding assistants or developing AI agents Strong written and verbal communication skills Self-motivated, organised and comfortable working in a dynamic environment Benefits 25 days holiday (in addition to 8 bank holidays) Hybrid working with high flexibility and the opportunity to work remotely up to 90% of the time Company contributory pension scheme A supportive, driven culture and a great team with an outstanding mix of talent and experience A dynamic environment in which you can personally learn, develop and make an impact Opportunity to work on a wide range of analytics, AI, data science and software projects Early exposure to real client challenges and production technology used by major consumer-facing businesses
Наблюдалась 2026-09-15, впервые 2026-09-14, источник — Indeed.