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Machine Learning Specialist (Data Scientist)

Machine Learning Specialist (Data Scientist)

Hybrid

London, United kingdom

£ 100,000 /year

Junior

Full Time

05-01-2026

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Skills

Communication Python Monitoring Test Training Windows Machine Learning AWS Data Science Mathematics

Job Specifications

Data Scientist | Machine Learning & Financial Engineering | Permanent | London 3 days a week | up to £100k per annum

Experience Level: 2+ Years Technical Stack: Python, AWS, Machine Learning

The Opportunity

We are seeking a proactive and analytically-driven Data Scientist to revolutionise the way our client process and validate complex financial data.

In this role, you will lead the transition from a manual, prototype-based cleaning process to a fully automated, scalable Machine Learning pipeline. You will be responsible for identifying outliers within large-scale datasets, ensuring the accuracy of data, and building a system that learns and improves through a continuous human-in-the-loop feedback mechanism.

Key Responsibilities

Model Design & Development: Design, build, train, and validate sophisticated ML models (including Random Forests and Boosted models) to automatically flag "bad" data across multiple dimensions.
Pipeline Automation (AWS): Build robust, production-ready data pipelines within the AWS ecosystem (S3, Lambda, etc.) to process high daily volumes of valuation data within tight windows.
Explain ability & Confidence: Develop methods to measure model confidence and provide clear reasoning for valuation decisions. You will ensure the system flags borderline cases for expert review to maintain high integrity.
Continuous Learning: Implement feedback loops where human corrections are automatically integrated into training data, allowing the model to evolve and improve accuracy over time.
Collaborative Innovation: Generate and test hypotheses to drive incremental progress, working closely with both technical teams and business stakeholders.

Required Skills & Experience

Commercial Experience: 2–5 years in a quantitative or data science role. Focus on Machine learning during this period
Technical Proficiency: Strong mastery of Python and demonstrable experience deploying/monitoring models in an AWS production environment.
ML Expertise: Deep statistical understanding of machine learning techniques, specifically classification and optimisation techniques to manage trade-offs between related data points.
Analytical Mindset: Proven ability to surface features that drive decisions even when they are not directly observable from raw training data.
Communication: Ability to collaborate across technical and business functions, with the potential to grow into a client-facing capacity.

Preferred Qualifications

Education: Masters or Ph.D. in a highly quantitative field (Statistics, Financial Engineering, Computer Science, or Mathematics).
Industry Background: Any industry is considered but financial services would be a plus

About the Company

TalentHawk is an International technology search and delivery consultancy with IT vendor selection skills that provides end-to-end solutions to organisations seeking maximum benefit from their technology solutions. Our mission is to transform the performance of your business through the acquisition of top tier technology executives and the optimisation of your delivery strategies. Our distinct market positioning and unique insight into sourcing strategies and talent acquisition enables us to deliver outstanding results ac... Know more