Data Analyst (Decision Science & Experimentation)

Marks and Spencer plc (UK)
UK
1 day ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours

Tech stack

Data Analysis R (Programming Language) Statistical Hypothesis Testing Python (Programming Language) Machine Learning SQL Databases Pyspark

Job description

Experteer Overview In this role you will advance analytical work on high-value opportunities, collaborating with analysts, data scientists, product teams and stakeholders to drive better decisions. You will translate business questions into clear analytical objectives and plans, explore data to uncover drivers and value, and apply appropriate statistical and experimental methods. You will validate results and clearly communicate uncertainties to non-technical audiences while supporting impact assessment and decision-making. Pay / Benefits * Contribute to analytical work on high-value opportunities with cross-functional teams * Translate complex business questions into analytical objectives and analysis plans * Prepare, explore and analyze data to identify patterns and drivers of performance * Support design and application of statistical modelling, experiments and quasi-experiments to test hypotheses * Validate outputs and communicate findings, uncertainties and limitations clearly Tasks * Strong mathematical and statistical knowledge (probability, inference, regression, experimental design) * Exposure to advanced analytical/machine learning methods and understanding of applicability and limitations * Structured problem-solving with real-world data and ambiguity * Clear communication to non-technical audiences * Experience using a data-focused programming/analytical language (Python, R, SQL, PySpark) Key requirements * 20% colleague discount after probation * holiday entitlement with potential to buy extra days * discretionary bonus schemes * Defined Contribution Pension Scheme and Life Assurance * tailored induction and training programmes * wellbeing support and 24/7 Virtual GP

Requirements

  • Strong mathematical and statistical knowledge (probability, inference, regression, experimental design) * Exposure to advanced analytical/machine learning methods and understanding of applicability and limitations * Structured problem-solving with real-world data and ambiguity * Clear communication to non-technical audiences * Experience using a data-focused programming/analytical language (Python, R, SQL, PySpark) Key requirements * 20% colleague discount after probation * holiday entitlement with potential to buy extra days * discretionary bonus schemes * Defined Contribution Pension Scheme and Life Assurance * tailored induction and training programmes * wellbeing support and 24/7 Virtual GP

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