26 to 50 of 95 Feature Engineering Jobs in the UK

specialists and external data suppliers. Please see full Job Description and Person Specification. Person Specification Knowledge and Experience Practical application expertise of managing data engineering projects and processes including data wrangling methods, models, data structures, and data formats such as JSON, XML and XSD. Machine learning for engineering … with relational SQL and databases. Experience with Azure tech stack such as Fabric, Data Factory, Synapse Analytics, Databricks and Lakehouses. Experience in building data engineering projects in Fabric. Knowledge of data warehousing and modelling concepts such as CDC/SCD. Ability to troubleshoot and solve numerical and technical problems. … complex organisation. Recent and ongoing continuous professional and personal development action and activity. Planning, objective setting and experience of performance management that incorporates Data Engineering and Data Science. Knowledge of Data Protection, legislation and directions that support the provision of data for counter fraud purposes. Experience in project delivery More ❯

innovation and leadership, this is the role you’ve been waiting for. Join a fast-growing Tech for Good Marketplace as their new ML Engineering Leader , where you’ll be at the forefront of AI-driven product development, building a skilled team, and driving the ML | Data Science | AI … vision for the business. What You'll Do: Develop and lead the ML Engineering | AI strategy as the company looks to drive a new period of experimentation & innovation with a personalised customer experience at the forefront of their plans. Lead and grow a team of ML engineers, fostering a … with software engineers, product managers, and business teams to define ML-driven solutions. Stay up-to-date with advancements in ML, AI, and data engineering best practices. Drive best practices in model explainability, bias mitigation, and ethical AI principles. What We’re Looking For: 5+ years of experience in More ❯

NLP tasks. Relationship Extraction: Evaluating different models for use-case specific RE, such as ATG. Document and text Classification Data Science: Data clustering algorithms, feature engineering Evaluate and integrate new technologies and models. Cross-team collaboration, identifying innovations and architecting solutions. Provide leadership and technical direction to various More ❯

Management and Preparation Work with Data Engineers to prepare clean, reliable datasets for analysis and modeling Implement data quality checks and validation procedures Perform feature engineering to optimize model performance Develop efficient data processing pipelines for model training and deployment Document data transformations and analytical methodologies 3. Cross More ❯

as TensorFlow, PyTorch, or Scikit-learn. Expert-level experience in Power BI for advanced visualisations, ML model interpretation, and KPI tracking. Deep knowledge of feature engineering, model deployment, and MLOps best practices. Experience with big data processing (Spark, Hadoop) and cloud-based data science environments. Other: Ability to … integrate ML workflows into large-scale data pipelines. Strong experience in data preprocessing, feature selection, and statistical modelling. Experience communicating complex findings to both technical and non-technical stakeholders. If you are interested and looking for your next role, please apply directly or email . More ❯

as TensorFlow, PyTorch, or Scikit-learn. Expert-level experience in Power BI for advanced visualisations, ML model interpretation, and KPI tracking. Deep knowledge of feature engineering, model deployment, and MLOps best practices. Experience with big data processing (Spark, Hadoop) and cloud-based data science environments. Other: Ability to … integrate ML workflows into large-scale data pipelines. Strong experience in data preprocessing, feature selection, and statistical modelling. Experience communicating complex findings to both technical and non-technical stakeholders. If you are interested and looking for your next role, please apply directly or email (url removed More ❯

deliver enterprise-grade data solutions, supporting high-impact business use cases across multiple domains. JOB ACCOUNTABILITIES Define and drive the future direction of data engineering and analytics practices, ensuring alignment with business goals and technological advancements. Design and implement sophisticated data pipelines and transformations, delivering curated, high-quality datasets … documentation and observability of analytical pipelines. Lead collaboration with BI Analysts and Data Scientists to refine methodologies, enhance reporting, and deliver scalable, production-ready feature engineering code. Drive engagement with business stakeholders, effectively communicating complex technical concepts in a clear, accessible manner to align analytics engineering initiatives More ❯

Each team member is approachable and committed to lending a hand, creating an environment where everyone feels supported and valued." - Sreekant, VP of API Engineering The team you'll work with: Reporting to the Director of AI, this is a high-impact role where your expertise will directly shape … Develop, test, deploy, and maintain machine learning models and algorithms, ensuring their scalability, robustness, and performance in production. Data Analysis & Optimization: Conduct data preprocessing, feature engineering, and exploratory analysis to optimize AI/ML models. Pipeline Development & Enhancement: Design, build, and enhance efficient machine learning pipelines, ensuring their … machine learning to identify new opportunities and techniques. To be a successful match you must have: 1+ years in a Machine Learning or ML Engineering role, with hands-on experience in deep learning frameworks (e.g., TensorFlow, PyTorch). Motivated recent graduates are encouraged to apply! A degree in Mathematics More ❯

such as pytest to ensure code quality and reliability. Experience with generative AI models, including GANs, VAEs, or transformers. Solid understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes, Amazon EKS). Excellent problem-solving skills and More ❯

mining techniques, with a focus on applications in text analysis or scientific data, including knowledge of forecasting, A/B testing, entity extraction, and feature engineering. Proficiency in programming languages such as Python, R, and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of More ❯

/ML solutions tailored to business needs. Lead the full model lifecycle: problem formulation, data exploration, model development, validation, deployment, and monitoring. Collaborate with engineering and product teams to embed models into production systems and deliver end-to-end solutions. Act as a technical leader and mentor within the … Scikit-learn, TensorFlow, PyTorch, etc. Hands-on experience with MLOps tools and practices: model tracking, drift detection, continuous learning. Strong background in data processing, feature engineering, and scalable ML pipelines. Experience working in cloud environments (Azure preferred) and with containerization tools (Docker, Kubernetes). Demonstrated success engaging with … environments. Desirable: Experience in the insurance or financial services domain. Familiarity with explainable AI (e.g., SHAP, LIME) and responsible AI practices. Knowledge of software engineering principles (CI/CD, version control, testing). Benefits A high-autonomy role with substantial influence over AI strategy and execution. Opportunities for career More ❯

build predictive models, and drive data-informed decisions across the organization. You will work closely with cross-functional teams, including [mention relevant teams like Engineering, Product, Marketing, etc.], to understand their needs and deliver impactful data-driven solutions. This is an exciting opportunity to contribute to [mention specific areas … statistical techniques, machine learning algorithms (e.g., regression, classification, clustering, deep learning), and data mining methods to analyze data, identify patterns, and build predictive models. Feature Engineering: Develop and implement effective features from raw data to improve model performance. Model Evaluation and Deployment: Evaluate the performance of models using More ❯

with world-class expertise in machine learning, statistics, optimization and stochastic control. These advisors include AI Labs co-head Stephen Boyd (Samsung Professor of Engineering at Stanford), Emmanuel Candes, Trevor Hastie, and Mykel Kochenderfer who dedicate time in our Palo Alto office and provide advice and guidance for all … problems. Build and maintain tools and services supporting the full model development lifecycle for statistical models, machine learning, optimization, and deep learning models (e.g., feature engineering, backtesting and simulation, validation, deployment). Maintain and monitor production models and experimentation. Tune performance in both single-threaded and distributed environments. … Enforce high-quality patterns and practices for maintaining model pipelines. Requirements 7+ years in software engineering, with 3+ years in API-backed ML deployment. Strong programming language skills in Python. Significant experience with SQL (e.g., RDBMS, Spark, Presto, or BigQuery). Experience with machine learning, optimization, and data manipulation More ❯

and innovate on methods like Bayesian neural networks , variational autoencoders , diffusion models , and Gaussian processes for modern AI use cases. Collaborate closely with product, engineering, and business teams to build end-to-end modeling solutions. Conduct deep-dive statistical and machine learning analyses, simulations, and experimental design. Stay current … programming tools. Hands-on experience with classical ML and modern techniques, including deep learning , transformers , diffusion models , and ensemble methods . Solid understanding of feature engineering, dimensionality reduction, model construction, validation, and calibration. Experience with uncertainty quantification and performance estimation (e.g., cross-validation, bootstrapping, Bayesian credible intervals). … Spark, Pandas). Ability to translate ambiguous business problems into structured, measurable, and data-driven approaches. Preferred Qualifications: M.Sc or PhD in Statistics, Electrical Engineering, Computer Science, Physics, or a related field. Background in generative modeling , Bayesian deep learning , signal/image processing , or graph models . Experience applying More ❯

and innovate on methods like Bayesian neural networks , variational autoencoders , diffusion models , and Gaussian processes for modern AI use cases. Collaborate closely with product, engineering, and business teams to build end-to-end modeling solutions. Conduct deep-dive statistical and machine learning analyses, simulations, and experimental design. Stay current … programming tools. Hands-on experience with classical ML and modern techniques, including deep learning , transformers , diffusion models , and ensemble methods . Solid understanding of feature engineering, dimensionality reduction, model construction, validation, and calibration. Experience with uncertainty quantification and performance estimation (e.g., cross-validation, bootstrapping, Bayesian credible intervals). … Spark, Pandas). Ability to translate ambiguous business problems into structured, measurable, and data-driven approaches. Preferred Qualifications: M.Sc or PhD in Statistics, Electrical Engineering, Computer Science, Physics, or a related field. Background in generative modeling , Bayesian deep learning , signal/image processing , or graph models . Experience applying More ❯

to real-world problems. A working knowledge of the state-of-the-art methods and best practices in data science, such as data preprocessing, feature engineering, model selection, validation, evaluation, and deployment. Ability to incorporate approaches from published academic papers into solutions/options. We will also be … events, a 2-day Summer event and 4 Newton-sponsored weekends a year. Seniority level Mid-Senior level Employment type Full-time Job function Engineering and Information Technology Industries Business Consulting and Services #J-18808-Ljbffr More ❯

modern online experiences should adapt to the needs and preferences of individual users? Are you fascinated by data, machine learning techniques, and software systems engineering? Do you love building creative, high-scale distributed systems using a diverse set of state of the art technologies? Our team wants to talk … team of ML Engineers and ML Scientists to operationalise ML models in production. You build scalable, high-performance systems for model development, data ingestion, feature engineering, inference, and monitoring/evaluation. You provide an accurate time estimates for your scope of work, turn it into code, and deliver … You advocate for quality coding. Write secure, stable, testable, maintainable code with minimal defects. Who you are 2+ years experience in ML and software engineering for Bachelor’s, 1+ years for Master’s Developed software in a team environment of at least 5 engineers (agile, version control, etc.). More ❯

structures to other ESP modeling tools. Qualifications EXPERIENCE/QUALIFICATIONS/EDUCATION REQUIRED Educational Requirements Bachelor's and/or master's in electrical engineering, economics, mathematics, or a related quantitative field (data science or data engineering emphasis desired). Required Work Experience 3-5 years of experience … high-performance computing environments. Experience with extracting, transforming, and loading processes and tools for handling large-scale datasets. Demonstrated ability to develop and deploy Feature Engineering and Modeling applications to data platforms built on Databricks or similar platforms and platform components (e.g., Snowflake, ML Flow, Airflow, etc.). More ❯

for end-to-end Machine Learning Scientists that have a strong background and experience in machine learning pipeline going through business understanding, data exploration, feature engineering, model building, performance evaluation, testing and production deployment. Our Product Analytics team is at the heart of data-driven decision-making, empowering … partner closely with product managers and business leaders to uncover insights, measure impact, and drive strategy. By analysing player behaviour, identifying trends, and evaluating feature performance, our team ensures that every decision is informed by robust, actionable data. Together, we fuel innovation and help deliver personalised, engaging experiences that … are looking for people who can support our ethos. To apply to this post, you will have: MSc in Computer Science/Statistics/Engineering or a related field with a focus on applied statistics, AI, machine learning, or related fields with experience working with predictive and probabilistic models More ❯

record of leading successful AI projects. Proficiency in AI and machine learning frameworks and programming languages (e.g., Python). Strong expertise in data preprocessing, feature engineering, and model evaluation. Excellent problem-solving and critical-thinking skills. Effective leadership, communication, and team management abilities. A passion for staying at More ❯

unstructured datasets, leveraging AWS big data services . Develop ML pipelines using AWS services such as SageMaker, Lambda, Glue, Redshift, and Athena . Implement feature engineering, model training, and hyperparameter tuning for scalable ML solutions. Collaborate with data engineers and analysts to integrate ML models into production. Ensure More ❯

record of leading successful AI projects. Proficiency in AI and machine learning frameworks and programming languages (e.g., Python). Strong expertise in data preprocessing, feature engineering, and model evaluation. Excellent problem-solving and critical-thinking skills. Effective leadership, communication, and team management abilities. A passion for staying at More ❯

record of leading successful AI projects. Proficiency in AI and machine learning frameworks and programming languages (e.g., Python). Strong expertise in data preprocessing, feature engineering, and model evaluation. Excellent problem-solving and critical-thinking skills. Effective leadership, communication, and team management abilities. A passion for staying at More ❯

record of leading successful AI projects. Proficiency in AI and machine learning frameworks and programming languages (e.g., Python). Strong expertise in data preprocessing, feature engineering, and model evaluation. Excellent problem-solving and critical-thinking skills. Effective leadership, communication, and team management abilities. A passion for staying at More ❯

model performance Deep learning Super learners Targeted learning Target maximum likelihood estimation Target trial emulation and other causal inference applications Causal modelling Predictive modelling Feature engineering Natural language processing Large language models NB Candidates to please note that VISA sponsorship is not supported for this role. More ❯