1 to 25 of 42 Feature Engineering Jobs in London

practices, serving as a data engineer/machine learning engineer in a technology development and delivery capacity. With your expertise in computer science, computer engineering, cloud, and data transformation (ETL & feature engineering), you will help build and shape McKinsey's scientific AI offering. As a member of … assets, and building the firm's reputation in your area of expertise. Your Impact You will leverage your expertise in data/machine learning engineering and product development to address complex client problems through part-time staffing, support the development of engineering roadmaps for cell-level initiatives, and … AI prototypes into deployment-ready solutions. By working directly with client delivery teams, you will ensure seamless implementation of these solutions. You will translate engineering concepts and design decisions for senior stakeholders, write optimized code to enhance McKinsey's AI Toolbox, and codify methodologies for future deployment. Collaborating with More ❯

analysis, statistical models, machine learning) using modern data science tools (Notebooks, Clouds). Design and implementation of machine learning models, metrics, and application of feature engineering techniques applied to customer problems. Support pre-sales in business opportunities and the engineering teams in the implementation of production-ready … models to help test hypotheses. Communicate findings effectively to an audience of engineers and executives. Required Qualifications: Bachelor's Degree in Computer Science/Engineering, Applied Math, Statistics, Physics or other related quantitative areas. Advanced oral and written communication skills in English. Ability to understand mathematical models and algorithms … use of the best frameworks for machine learning pipelines, data visualization, manipulation and transforming, models training and evaluation, and models deployment. Experience with common feature engineering techniques and machine learning algorithms for Supervised and Unsupervised Learning. Experience with Natural Language Processing (NLP and NLU). Experience using Generative More ❯

analysis, statistical models, machine learning) using modern data science tools (Notebooks, Cloud platforms). Design and implement machine learning models, develop metrics, and apply feature engineering techniques tailored to customer problems. Support pre-sales efforts and assist engineering teams in deploying production-ready machine learning solutions. Evaluate … segmentation, using machine learning models to test hypotheses. Communicate findings effectively to engineers and executives. Required Qualifications: Bachelor's Degree in Computer Science/Engineering, Applied Math, Statistics, Physics, or related quantitative fields. Proficiency in English, both oral and written. Ability to understand and implement mathematical models and algorithms … visible progress updates to the team. Proficiency in Python or R, SQL, and relevant frameworks for machine learning, data visualization, and deployment. Experience with feature engineering and machine learning algorithms for Supervised and Unsupervised Learning (Regression, Classification, Clustering, etc.). Experience with Natural Language Processing (NLP and NLU More ❯

learning systems at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance Partner with stakeholders to propose innovative data products that leverage Trainline … Flow Have experience with agile delivery methodologies and CI/CD processes and tools Have a broad understanding of data extraction, data manipulation and feature engineering techniques Are familiar with statistical methodologies. Have good communication skills Nice to have Experience with LangGraph or LangChain Experience with transport industry More ❯

real-world problems, shipping results fast, all whilst meeting launch deadlines. Take ownership of end-to-end ML model development-from data preprocessing and feature engineering to training, testing, and deployment. Collaborate across teams to implement machine learning solutions into production systems, ensuring that models are scalable, reliable … machine learning, with a strong understanding of core ML algorithms and frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Hands-on experience with data preprocessing, feature engineering, and model training for real-world problems. Strong Python and Java programming skills and familiarity with NLP algorithms and libraries. Solid understanding More ❯

the heart of Central London and home to our Research Lab. The role We are seeking exceptional Engineers to join our newly established GenAI Engineering team. In this role, you will be at the forefront of developing and implementing cutting-edge AI solutions across G-Research, working on a … wide range of projects. As a key member of the GenAI Engineering team, you will collaborate with researchers, data scientists and business stakeholders to design, develop and deploy AI applications that drive innovation and efficiency throughout the organisation. Key responsibilities of the role include: Developing end-to-end AI … Who are we looking for? We are seeking candidates who are comfortable working both independently and in small teams on a variety of AI engineering challenges, with a focus on practical implementation and deployment of AI solutions. You will have the opportunity to work on diverse and challenging AI More ❯

will be headquartered at our Westminster, Colorado offices and is primarily an on-premises position. The Machine Learning Engineer will work closely with an engineering team composed primarily of aerospace and software engineers. The ideal candidate has a strong background in software development best practices, mathematics, and statistics, as … and implement state-of-the-art machine learning algorithms and techniques Design, develop, and deploy machine learning models and systems that can address various engineering problems and opportunities Perform data analysis, preprocessing, feature engineering, and model evaluation Optimize the performance, scalability, and reliability of machine learning solutions … of hands-on professional experience. Master's degree or PhD research may contribute to this experience. Bachelor's degree or higher in Computer Science, Engineering, Mathematics, Statistics, or related field Proficient with one or more machine learning model development frameworks, especially PyTorch or TensorFlow. Familiar with the basics of More ❯

then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: Proficiency in programming languages used in ML, such as Python/Java. Knowledge of software development best practices and methodologies. Experience with version control … learning principles, algorithms, and techniques. Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proficiency in data preprocessing, feature engineering, and model evaluation. Knowledge of ML model deployment and serving strategies, including containerization and microservices. Familiarity with ML lifecycle management, including versioning … in a similar role, with an excellent understanding of AI/ML lifecycle management. Strong experience deploying and productionising ML models. Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies. Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ More ❯

then put into practice and become certified on various Cloud (and related) technologies that will help you to develop your own toolkit. Requirements Software Engineering: • Proficiency in programming languages used in ML, such as Python/Java. • Knowledge of software development best practices and methodologies. • Experience with version control … learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle management, including versioning … in a similar role, with an excellent understanding of AI/ML lifecycle management. • Strong experience deploying and productionizing ML models. • Familiarity with data engineering concepts, including data pipelines, ETL processes, and big data technologies. • Excellent problem-solving skills and the ability to troubleshoot complex issues in AI/ More ❯

teams to understand business requirements and deliver data-driven insights. Design and build scalable data pipelines and ETL processes. Perform data exploration, preprocessing, and feature engineering. Conduct statistical analysis and machine learning model development. Communicate findings and insights to stakeholders through data visualization and reports. Stay current with industry More ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

experiences: Mandatory Experience developing and deploying models or tools using Python. Proficiency with standard statistical and machine learning techniques. Strong understanding of data wrangling, feature engineering, and visualisation techniques. Experience with relational databases and proficiency in SQL. Good communication skills - able to explain technical concepts to non-technical More ❯

to £130,000 | Remote (UK) 167 Solutions Ltd is hiring on behalf of a leading organisation seeking a Senior Data Engineer to join their engineering team. This role is ideal for an experienced data engineer who thrives in a dynamic environment and is eager to design, develop, and maintain … Airflow, AWS Glue, and Amazon Athena . Work with cloud-native technologies to support scalable, serverless architectures. Collaborate with data science teams to streamline feature engineering and model deployment. Ensure data governance, lineage, and compliance best practices. Mentor and support team members in data engineering best practices … . Skills & Experience Required 6+ years of experience in data engineering within large-scale digital environments. Strong programming skills in Python, SQL, and Spark (SparkSQL) . Expertise in Snowflake and modern data architectures. Experience designing and managing data pipelines, ETL, and ELT workflows . Knowledge of AWS services such More ❯

knowledge of Acadian's processes and pertinent new research. Explore structured and unstructured datasets with a focus on data preparation, transformation, outlier detection, and feature engineering. Collaborate on the design of ESG constraints for client-driven investment solutions, help build predictive models and design interactive data applications. We're More ❯

only leverage a fraction of it for predictive tasks. This is because traditional machine learning is slow and time consuming, taking months to perform feature engineering, build training pipelines, and achieve acceptable performance. At Kumo, we are building a machine learning platform for data lakehouses, enabling data scientists … best practices, etc. so that they increase usage across a larger number of internal workloads. Provide market and customer feedback to the Product and Engineering team to refine feature specifications and the product roadmap. Create broader processes for each customer to go through to ensure we can drive More ❯

Proficient in Python programming and SQL, with experience in production-level code and data analysis libraries. · Familiar with ML Ops, model development workflows, and feature engineering techniques. · Capable of manipulating data and developing models accessible for business use, with experience in Azure AI Search. · Adept with software development More ❯

Proficient in Python programming and SQL, with experience in production-level code and data analysis libraries. · Familiar with ML Ops, model development workflows, and feature engineering techniques. · Capable of manipulating data and developing models accessible for business use, with experience in Azure AI Search. · Adept with software development More ❯

Proficient in Python programming and SQL, with experience in production-level code and data analysis libraries. Familiar with ML Ops, model development workflows, and feature engineering techniques. Capable of manipulating data and developing models accessible for business use, with experience in Azure AI Search. Adept with software development More ❯

Proficient in Python programming and SQL, with experience in production-level code and data analysis libraries. Familiar with ML Ops, model development workflows, and feature engineering techniques. Capable of manipulating data and developing models accessible for business use, with experience in Azure AI Search. Adept with software development More ❯

delivering innovative, tailored data driven solutions combined with insight generation. Key responsibilities Advanced Analytics Delivery: Lead end‑to‑end data analytics projects—data exploration, feature engineering, model development (ML/AI), validation, and deployment—tailored to solving client business problems Analytics Framework & Playbooks: Co‑create repeatable playbooks for More ❯