Experian Ventures powers global opportunities while creating new value with data and analytics. We look for firms who will deliver the solutions of tomorrow to simplify credit and lending, reduce complexity in specialized verticals, automate and secure...
About the role
You have experience working as a data scientist (or in a similar role), applied machine learning, and Python programming. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- You will work with product, engineering, and business teams to turn fuzzy ideas into clear problem statements, assumptions, and success metrics
- You will design and run experiments to evaluate GenAI systems, including baseline comparisons, error analysis, and understanding failure modes
- Help refine GenAI solutions, using modern development practices and AI-assisted coding tools to iterate quickly
- Communicate results, including trade-offs, limitations, and recommendations for what to do next
- Share insights with the team and spend ~10% of your time on learning and knowledge sharing
- You are comfortable working with incomplete information, and enjoy figuring things out through exploration and experimentation
More about this role
Role Overview
The Generative AI Centre of Expertise (GenAI CoE) at Experian helps teams across Experian's UK business. It improves products using Generative AI, machine learning, and automation. The centre has a focus on responsible, measurable impact.
This is a mid-level, hybrid secondment role for a data scientist who enjoys hands-on work and wants to grow into AI engineering. You'll report into the Head of Machine Learning and work across two connected areas:
- Experimentation and evaluation (data science): framing problems, designing experiments, defining success metrics, analysing results, and understanding model/system behaviour in product contexts
- AI engineering: build GenAI systems (prototypes through to production-ready components), supported by experienced colleagues
A big part of the job is choosing the right approach — when GenAI is valuable, and when simpler analytics or ML is the better answer.
- You will work with product, engineering, and business teams to turn fuzzy ideas into clear problem statements, assumptions, and success metrics
- You will design and run experiments to evaluate GenAI systems, including baseline comparisons, error analysis, and...
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