Innovation Data Scientist

Markerstudy Group; United Kingdom; On-site; GBP 50,000 - 75,000; Full time

Job summary

Join a leading company as an Innovation Data Scientist, where you'll blend hands-on data science with strategic exploration in Generative AI. You will be responsible for delivering data-driven solutions and working with a multidisciplinary team to shape the future of technology within the organization. Your expertise will help drive innovation and AI literacy across the organization.

Qualifications

• Significant experience in data science, ideally in a mid or senior capacity.
• Strong SQL skills with experience in structured and unstructured data.
• Familiarity with innovation environments and GenAI applications.

Responsibilities

• Identify and deliver data-driven proofs of concept aligned with innovation strategy.
• Lead design and evaluation of innovative data-driven solutions.
• Collaborate with stakeholders to inform solution approaches.

Skills

Data Science

Machine Learning

Python

SQL

Cloud Platforms

NLP

Generative AI

Collaboration

Tools

Azure

GCP

LangChain

Databricks

Docker

Job description

Role Purpose:

The Innovation Data Scientist plays a key role in the Group's Innovation function, helping to shape and deliver the Technology Innovation and GenAI roadmap. This role blends hands-on data science and engineering with strategic exploration, focusing on the practical application of emerging technologies - particularly Generative AI - to solve real business challenges. Working within a multidisciplinary team, the Innovation Data Scientist will lead the design, prototyping, and evaluation of innovative data-driven solutions, helping to inform and influence the Group's future technology direction.

Key Accountabilities and Responsibilities:
• Identify and deliver a pipeline of data-driven proofs of concept (PoCs) and early-stage projects aligned with the Innovation strategy.
• Act as a technical SME for data science and GenAI technologies, contributing to tool selection and architectural decisions.
• Collaborate with business stakeholders, architects, engineers, and data SMEs to shape priorities and solution approaches.
• Design, build, and test prototypes using modern data science and ML techniques, with a focus on scalability and real-world impact.
• Define success criteria and evaluate the performance of models and solutions, including lessons learned and recommendations for scale-up.
• Support the rollout of successful innovations across business functions and applications.
• Contribute to the development of responsible AI practices, including governance, testing, and documentation.
• Help build AI literacy across the organisation, co-developing new ways of working and sharing insights with stakeholders.
• Stay current with emerging technologies and trends in data science, GenAI, and ML, bringing fresh thinking to the team.

Skills, Experience and Knowledge:
• Significant experience in a data science, ML engineering, or advanced analytics role, ideally in a mid or senior capacity.
• Proficiency in Python or R, with experience as a polyglot or in multi-language environments.
• Strong SQL skills and experience working with structured and unstructured data.
• Experience with cloud platforms such as Azure and GCP for deploying data science workloads.
• Solid understanding of machine learning methods (supervised and unsupervised), model evaluation, and lifecycle management.
• Experience with NLP tasks (e.g., sentiment analysis, entity recognition) and LLMs (e.g., GPT, Gemma).
• Familiarity with LangChain (or equivalents), LLMOps, Databricks, and API management.
• Understanding of TDD, modular design, authentication, version control (e.g., Git), Docker, and CI/CD pipelines.
• Strong analytical and problem-solving skills, with a focus on experimentation and measurable outcomes.
• Excellent communication and collaboration skills, with the ability to work across disciplines.
Preferred:
• Experience with innovation accelerators or R&D environments.
• Passion for GenAI and a strong understanding of its potential business applications.
• Experience in regulated industries such as insurance or financial services.