Senior Applied Data Scientist

Overview

In this role you apply advanced data science to distill complex problems into actionable insights that deliver measurable client value. You will join a high-caliber team working with major retailers to build reusable, scalable models and applications. You’ll tackle category management challenges for Tesco and other clients, driving impact through data-driven solutions. You collaborate across functions to shape innovative approaches and tangible outcomes. This is a mission-driven opportunity to influence decision-making at scale with cutting-edge techniques.

Pay / Benefits

• flexible working hours
• birthday off
• comprehensive rewards package
• personal flexibility
• investment in cutting-edge technology
• diversity and inclusion networks

Responsibilities

• Implement, support, and develop complex models and applications for clients
• Collaborate with client leadership and cross-functional teams to deliver reusable, scalable solutions
• Drive change by shaping innovative data-driven approaches and defining project direction
• Solve challenging problems in category management and related retail analytics
• Translate technical work into clear, measurable business impact for clients

Key requirements

• Degree in Statistics, Mathematics, Physics, Economics, or related quantitative field
• Strong programming skills in Python and SQL; PySpark experience advantageous
• Experience with version control tools (e.g. Git)
• Solid understanding of analytical technologies, tools, and techniques
• Excellent logical thinking and problem-solving abilities
• Strong communication skills for explaining complex concepts to non-technical audiences
• Proven experience in statistical modelling and applying data science to real client problems
• Passion for connecting technical work to real customer outcomes and measurable impact
• Ability to initiate new workstreams with clear direction and stakeholder alignment
• Background in retail analytics, especially category management, is advantageous

• clear communication
• problem solving
• collaboration across functions
• Python
• SQL
• PySpark

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