Data Scientist

• Building and maintaining scalable pipelines to ingest, clean and structure research, commercial, behavioural and product data
• Developing reproducible analytical datasets that power internal reporting and client insight outputs
• Writing and maintaining dbt models and SQL transformations to ensure consistent, well-documented data logic
• Implementing automated data quality checks and monitoring to maintain accuracy and trust
• Translating stakeholder questions into clear metrics, analytical definitions and data views
• Producing recurring insight outputs such as trends, cohort analysis, segmentation and profiling
• Supporting ad-hoc analytical deep dives for product, research and client teams
• Building reporting layers and enabling self-serve analytics for non-technical users
• Defining and monitoring KPIs related to platform health, insight quality and outcomes
• Collaborating closely with engineering, product and client-facing teams to align analytics with business and research needs, Should we both wish to proceed, we will submit your details to the client and be in touch regarding the outcome and any further steps.

You'll be an experienced analytics professional who enjoys working with messy, real-world data and turning it into clear, actionable insight. You'll be comfortable owning datasets end-to-end and communicating findings to a wide range of stakeholders.

We're looking for someone with:

• 3+ years' experience in data science, analytics, BI or research-focused data roles
• Strong SQL and Python skills
• Proven experience building ETL/ELT pipelines and analytical datasets from ingestion through to reporting
• Hands-on experience with dbt or similar data transformation tools
• Confidence working across multiple data sources and data types
• Strong communication skills, with the ability to turn ambiguous questions into structured analytical outputs

Desirable (but not essential) experience includes:

• Market research, consumer insight or behavioural data
• Cloud data tooling (AWS or Azure environments)
• Document-based databases such as MongoDB
• Dashboarding and BI tools (e.g. Power BI, Tableau, Looker, Mode, Metabase)
• Experience working in fast-paced or startup-style environments, * Stage 2 - 1-2 hour technical discussion focused on skills, problem-solving approach, and real-world experience (remote)
• Stage 3 - 30-minute interview with CTO or Senior Leadership team covering culture, communication and alignment with company vision and goals (remote), * ETL
• Python
• SQL
• DBT
• Data Science
• ELT

• Annual bonus up to two months' salary based on company performance
• Private medical insurance via Vitality
• Nest pension contributions
• Employee referral bonuses
• Regular virtual and in-person team events
• Recognition awards for outstanding contributions
• A chance to shape the analytics backbone of the next generation of AI-powered consumer intelligence

Our client is an AI-led technology company redefining how organisations generate consumer insight. Using advanced GenAI and Large Language Models, they are transforming qualitative research through automated moderation, real-time insight generation, and intelligent conversational systems. Operating on a modern cloud stack across AWS and Azure, they are scaling rapidly and investing heavily in production-grade AI capabilities. This is an opportunity to join a product-focused AI team building real-world, high-impact GenAI solutions. How you'll spend your day You'll take ownership of the analytical backbone that underpins a data-driven platform and its insight delivery. This role is focused on data preparation, analytics and insight enablement, turning complex, real-world data into trusted datasets and meaningful outputs that support dashboards, client deliverables and product decisions.