15 of 15 Feature Engineering Jobs in the South East

Responsibilities Lead the design, development, and maintenance of credit risk and affordability models using bureau, open banking, and behavioural data Own the full model lifecycle from data sourcing and feature engineering to validation, deployment, and monitoring Design and run A/B and champion/challenger tests to improve performance across approval rates, losses, and customer experience Analyse … credit performance data to deliver insights that guide strategic decisions Mentor and support junior analysts/data scientists as the team expands Collaborate with data engineering to deploy models into production Work closely with stakeholders to define goals, communicate findings, and translate model outputs into business value About You You are an analytical thinker with a passion for using … data to drive credit decisioning. You bring hands-on experience building machine learning models for consumer credit and understand the nuances of data preparation, feature selection, and model validation in high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn More ❯

Responsibilities Lead the design, development, and maintenance of credit risk and affordability models using bureau, open banking, and behavioural data Own the full model lifecycle from data sourcing and feature engineering to validation, deployment, and monitoring Design and run A/B and champion/challenger tests to improve performance across approval rates, losses, and customer experience Analyse … credit performance data to deliver insights that guide strategic decisions Mentor and support junior analysts/data scientists as the team expands Collaborate with data engineering to deploy models into production Work closely with stakeholders to define goals, communicate findings, and translate model outputs into business value About You You are an analytical thinker with a passion for using … data to drive credit decisioning. You bring hands-on experience building machine learning models for consumer credit and understand the nuances of data preparation, feature selection, and model validation in high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn More ❯

from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements and business objectives into effective data science solutions, working closely with the Delivery Manager and Engineering teammates (Software and Data Engineers) within your modelling team. Perform data cleaning, exploratory data analysis (EDA), feature engineering, and model evaluation to support continuous model improvement. Write More ❯

relevance. Build production-ready Python code and integrate models into user-facing applications. Monitor and refine model performance post-deployment, making improvements based on feedback. Collaborate with product and engineering teams to deliver solutions aligned with business goals. Role Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python … core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid understanding of machine learning algorithms and statistical modelling techniques. A degree in Computer Science, Statistics, Machine Learning, Engineering, Physics, or a related More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

be doing: Designing and maintaining scalable data pipelines and infrastructure to support structured, analysis-ready data Designing and deploying end-to-end machine learning models from data preparation and feature engineering to model training, evaluation, and monitoring Overseeing a team of three data analysts and collaborating closely with business analysis and developers across William Reed Setting out a More ❯

science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to … and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and client stakeholders Bachelor’s or Master’s degree in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science) from a strong university Excellent communication skills and a collaborative mindset Please note: This role cannot offer VISA sponsorship More ❯

science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to … and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and client stakeholders Bachelor’s or Master’s degree in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science) from a strong university Excellent communication skills and a collaborative mindset Please note: This role cannot offer VISA sponsorship More ❯

science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to … and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and client stakeholders Bachelor’s or Master’s degree in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science) from a strong university Excellent communication skills and a collaborative mindset Please note: This role cannot offer VISA sponsorship More ❯

production-level solutions Troubleshoot and debug code Work with other teams to understand and solve business problems About you: Python (pandas, NumPy, scikit-learn): For data wrangling, modelling, and feature engineering SQL: For querying structured data sources Model Development & Validation: Experience with classification, unsupervised learning (e.g. outlier detection), and ranking models Machine Learning Deployment: Familiarity with containerised deployment More ❯

markets. Responsibilities: Lead the development and maintenance of credit risk and affordability models using bureau, open banking, and alternative behavioural data. Own end-to-end model lifecycle: data sourcing, feature engineering, model development, validation, and monitoring. Design and execute champion/challenger tests and A/B experiments to continuously improve approval rates, loss rates, and customer experience … performance data to generate actionable insight and support strategic decisions Mentor and develop a small team of analysts/data scientists as the team scales Work closely with Data Engineering to deploy models into production pipelines. Collaborate with stakeholders to define modelling goals and interpret model outcomes in a business context. Requirements: MSc or PhD Degree in Computer Science More ❯

markets. Responsibilities: Lead the development and maintenance of credit risk and affordability models using bureau, open banking, and alternative behavioural data. Own end-to-end model lifecycle: data sourcing, feature engineering, model development, validation, and monitoring. Design and execute champion/challenger tests and A/B experiments to continuously improve approval rates, loss rates, and customer experience … performance data to generate actionable insight and support strategic decisions Mentor and develop a small team of analysts/data scientists as the team scales Work closely with Data Engineering to deploy models into production pipelines. Collaborate with stakeholders to define modelling goals and interpret model outcomes in a business context. Requirements: MSc or PhD Degree in Computer Science More ❯

a plus, but not a hard requirement. Preferable experience in alpha research/signal generation, or worked on systematic trading strategy development. Deep understanding of data science practices e.g. feature engineering and signal combining. Bachelor's degree or higher in a Quantitative discipline e.g. Maths, Computer Science, Engineering, Physics, or Statistics. Compensation Competitive base salary. Offers can More ❯

success criteria. Support and mentor junior team members, fostering a collaborative environment. Independently manage client relationships and project expectations. Develop and deploy ML models, applying innovative approaches beyond basic feature engineering. Use Python, SQL, and Tableau for reporting and analysis within an AWS environment. Work closely with Data Engineering, Sales, and Market Research teams across the UK, US … meaningful insights to drive business decisions. Strong communication skills, with experience in managing client relationships. A degree in a relevant field such as Mathematics, Statistics, Economics, Psychology, Sociology, Physics, Engineering, or Computer Science (Master’s or PhD is a plus). Interest or experience in TV viewing data, media, or marketing analytics is beneficial but not essential. If this More ❯

the best tools into the tech stack. Prototyping, testing, and refining AI applications to improve accuracy and performance. Writing clean, modular Python code and performing rapid data processing and feature engineering. Identifying and prioritising opportunities for AI implementation based on business needs and feedback. Translating complex technical concepts into clear, accessible explanations for stakeholders. What we're looking for … Essential: Strong experience with Gen AI, NLP, and machine learning. Proven ability to create, train, and fine-tune LLMs/SLMs. Skills in prompt engineering and RAG (retrieval-augmented generation). Solid background in Python, Java, and database technologies (SQL/NoSQL). Experience in crawling/web scraping and API development. Experience with on-premise AI development (local More ❯