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Job Title: Lead Data Scientist
Contract Length: 12 months
Engagement Type: Umbrella/PAYE
Location: Reading or London – Hybrid role
About the Role:
KPMG is seeking a highly skilled and strategic Lead Data Scientist to spearhead internal data science initiatives that drive innovation, efficiency, and data-driven decision-making across the firm. This non-client-facing role is pivotal to enhancing internal operations, optimizing firmwide data assets, and supporting leadership with advanced analytics and AI-powered solutions. You will lead a small but growing team of data scientists and work closely with business units, IT, and data governance teams to shape and implement KPMG’s data science agenda from within.
Key Responsibilities:
- Strategy & Leadership
- Lead the design and execution of internal data science projects aligned with firmwide strategic goals.
- Act as a subject matter expert and advisor for senior stakeholders on the application of data science and AI within internal operations.
- Drive the adoption of best practices in machine learning, data engineering, and model governance.
- Solution Development
- Build and deploy scalable models and algorithms to solve operational challenges such as resource optimization, risk analytics, internal audit automation, and knowledge management.
- Leverage NLP, computer vision, time series forecasting, and other advanced techniques to derive insights from structured and unstructured internal data.
- Team Management & Mentorship
- Manage and mentor a team of data scientists, promoting technical excellence and continuous learning.
- Provide technical oversight and review of code, models, and solution design.
- Collaboration & Stakeholder Engagement
- Work with internal business units (e.g., HR, Finance, Compliance, IT) to gather requirements and prioritize data science opportunities.
- Collaborate with Data Engineering, Data Governance, and IT teams to ensure solutions are secure, ethical, and aligned with firmwide architecture and standards.
Key Skills & Experience:
- Proven experience in leading end-to-end data science projects in a complex organization.
- Expertise in Python and key libraries (e.g., pandas, scikit-learn, TensorFlow, PyTorch, etc.).
- Familiarity with cloud platforms (Azure preferred) and data platforms like Databricks or Snowflake.
- Strong understanding of ML lifecycle management (e.g., MLflow, model versioning, testing, retraining).
- Proficient in working with large datasets, SQL, and data wrangling.
- Experience in deploying models to production environments (e.g., using Docker, APIs, CI/CD pipelines).
- Strong stakeholder management and the ability to translate business needs into data science solutions.
- Understanding of responsible AI, data privacy, and ethical modelling practices.
- Experience working with internal corporate data (e.g., HR data, financial data, operational metrics).
- Background in supporting enterprise functions such as internal audit, risk, or knowledge management with AI tools.
- Exposure to change management or process transformation projects enabled by analytics.
KPMG Overview
KPMG is part of a global network of firms that offers Audit, Tax & Legal, Consulting, Deal Advisory and Technology services. Through the talent of over 16,000 colleagues, we bring our creativity and insight to our clients’ most critical challenges.
With offices across the UK, we work with everyone from small start-ups and individuals to major multinationals, in virtually every industry imaginable. Our work is often complex, yet our vision is simple: to be the clear choice for our clients, for our people and for the communities we work in.
