Senior Decision Scientist

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
Key people and teams I work within and outside of Tesco:
- Enterprise Analytics Senior Management
- Partners across the global Tesco business

People; budgets and other resources I am accountable for in my job:
- NA

Operational skills relevant for this job:
- Applied Math: Applied Statistics; Design of Experiments; Regression; Decision Trees; Forecasting; Optimization algorithms; Clustering; NLP
- Tech: SQL; Hadoop; Spark; Python; Tableau; MS Excel; MS PowerPoint; GitHub
- Business: Basic understanding of Retail domain
- Soft Skills: Analytical Thinking & Problem solving; Storyboarding; Articulate communication

Experience relevant for this job:
- 2 - 4 years' experience in data science application in Retail or CPG Preferred
- Functional experience: Marketing; Supply Chain; Customer; Merchandising; Operations; Finance or Digital

Requirements

Experience relevant for this job:
- 2 - 4 years' experience in data science application in Retail or CPG Preferred
- Functional experience: Marketing; Supply Chain; Customer; Merchandising; Operations; Finance or Digital

Operational skills relevant for this job:
- Applied Math: Applied Statistics; Design of Experiments; Regression; Decision Trees; Forecasting; Optimization algorithms; Clustering; NLP
- Tech: SQL; Hadoop; Spark; Python; Tableau; MS Excel; MS PowerPoint; GitHub
- Business: Basic understanding of Retail domain
- Soft Skills: Analytical Thinking & Problem solving; Storyboarding; Articulate communication