Job Summary:
Enable data driven decision making across the Tesco business globally by developing analytics solutions using a combination of math,
tech and business knowledge
In this job, I’m accountable for:
Following our Business Code of Conduct and always acting with integrity and due diligence and have these specific risk responsibilities:
- Understands business needs and in depth understanding of Tesco processes
- Builds on Tesco processes and knowledge by applying CI tools and techniques.
- Responsible for completing tasks and transactions within agreed KPI's
- Solves problems by analyzing solution alternatives
-Engaging with business & functional partners to understand business priorities, ask relevant questions and scope same into a analytical
solution document calling out how application of data science will improve decision making
- In depth understanding of techniques to prepare the analytical data set leveraging multiple complex data set sources
- Building Statistical models and ML algorithms with practitioner level competency
- Writing structured, modularized & codified algorithms using Continuous Improvement principles (development of knowledge assets and
reusable modules on GitHub, Wiki, etc) with expert competency
- Building easy visualization layer on top of the algorithms in order to empower end-users to take decisions - this could be on a
visualization platform (Tableau / Python) or through a recommendation set through PPTs
- Working with the line manager to ensure application / consumption and proactively identifying opportunities to help the larger Tesco
business with areas of improvement
- Keeping up-to-date with the latest in data science and retail analytics and disseminating the knowledge among colleagues
Refer "About the role"
Key people and teams I work with in and outside of Tesco:
People, budgets and other resources I am accountable for
in my job:
Enterprise Analytics Senior Management
NA
Partners across the global Tesco business
Operational skills relevant for this job:
Experience relevant for this job:
- Applied Math: Applied Statistics, Design of Experiments,
- 2 - 4 years experience in data science application in Retail or
Regression, Decision Trees, Forecasting, Optimization
CPG Preferred
algorithms, Clustering, NLP
- Functional experience: Marketing, Supply Chain, Customer,
- Tech: SQL, Hadoop, Spark, Python, Tableau, MS Excel, MS
Merchandising, Operations, Finance or Digital
Powerpoint, GitHub
- Agentic AI: Concepts of building Agents, RAG, LangGraph
- Business: Basic understanding of Retail domain
- Soft Skills: Analytical Thinking & Problem solving,
Storyboarding, Articulate communication