18 of 18 Remote Feature Engineering Jobs in London

AI. The team includes data strategists, consultants, data scientists and analysts that work alongside DEPT teams around the world across different services - from commerce, to full-funnel media, content engineering to internal operations. You will be solving some of the hardest and most challenging problems facing some of the best loved brands in the world - and doing this alongside … machine learning models for marketing attribution, customer prediction, segmentation, and recommendation systems with deep understanding of customer experience and marketing use-cases Implement end-to-end ML pipelines including feature engineering, model training, deployment, and monitoring Perform advanced statistical analysis including A/B testing, causal inference, and experimental design Deploy production ML systems with automated retraining, drift … on data and ML implementation, serving as a trusted advisor on data-driven decision making WHAT WE ARE LOOKING FOR MSc degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative field 3+ years of experience in data science and/or ML engineering roles Strong foundation in statistics and mathematics including probability theory, hypothesis More ❯

latency, and compute constraints. Apply 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 with emerging trends in generative … TensorFlow Probability , or similar probabilistic 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). Familiarity with database and data … processing tools (e.g., SQL, MongoDB, 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 probabilistic models in real-world More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

and prospects' questions, based on 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 Looking for Teammates With: Bachelor More ❯

Qualifications: PhD in a relevant discipline or Master’s plus a comparable level of experience Experience in Knowledge Graphs or Large Document Search Experience with traditional ML models and feature engineering. Strong Experience with fine tuning, modelling and deploying LLMs - experience with RAG, IR, NER etc would also be very beneficial Strong programming skills (e.g., Python) and experience with … modern ML frameworks (e.g., PyTorch, TensorFlow, LangChain). Collaborating with other Researchers, Product, Engineering and Business Stakeholders in an agile manner to demonstrate value and iterate with customer feedback. Please apply below for immediate consideration More ❯

Qualifications: PhD in a relevant discipline or Master’s plus a comparable level of experience Experience in Knowledge Graphs or Large Document Search Experience with traditional ML models and feature engineering. Strong Experience with fine tuning, modelling and deploying LLMs - experience with RAG, IR, NER etc would also be very beneficial Strong programming skills (e.g., Python) and experience with … modern ML frameworks (e.g., PyTorch, TensorFlow, LangChain). Collaborating with other Researchers, Product, Engineering and Business Stakeholders in an agile manner to demonstrate value and iterate with customer feedback. Please apply below for immediate consideration More ❯

drive innovation into the product development process. You will interpret your client’s objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently. You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level … of UK Security Vetting (DV), upon application. Key Responsibilities: You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below: Data Engineering tasks Manage the implementation and development of integrations between the data warehouse and other systems. Create deployable data pipelines that are tested and robust using … Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the business and your clients, establishing More ❯

drive innovation into the product development process. You will interpret your client’s objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently. You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level … of UK Security Vetting (DV), upon application. Key Responsibilities: You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below: Data Engineering tasks Manage the implementation and development of integrations between the data warehouse and other systems. Create deployable data pipelines that are tested and robust using … Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the business and your clients, establishing More ❯

skills – even better if these skills have been applied to threat detection, malware analysis, phishing and/or abuse detection. Experience building production-grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring. Experience designing and implementing anomaly detection, classification, clustering, and retrieval across vision and language models, ideally for identifying cyber threats (URLs, domains … fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI services at scale, particularly on AWS via Terraform. The package offered to the Senior/Principal AI Engineer will consist of More ❯

skills – even better if these skills have been applied to threat detection, malware analysis, phishing and/or abuse detection. Experience building production-grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring. Experience designing and implementing anomaly detection, classification, clustering, and retrieval across vision and language models, ideally for identifying cyber threats (URLs, domains … fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI services at scale, particularly on AWS via Terraform. The package offered to the Senior/Principal AI Engineer will consist of More ❯

skills – even better if these skills have been applied to threat detection, malware analysis, phishing and/or abuse detection. Experience building production-grade AI pipelines, including data ingestion, feature engineering, validation, model deployment, and monitoring. Experience designing and implementing anomaly detection, classification, clustering, and retrieval across vision and language models, ideally for identifying cyber threats (URLs, domains … fit to problem space, including scenarios where RAG is applicable. Incident response experience, and ability to work with large, noisy, and rapidly evolving threat datasets. Strong background in cloud engineering and containerisation (Docker, Kubernetes) with experience deploying AI services at scale, particularly on AWS via Terraform. The package offered to the Senior/Principal AI Engineer will consist of More ❯

What you will do In this role, you will provide technical leadership in the development of our Causal AI platform, guiding both the vision and execution within our Product Engineering team, which includes software engineers, data scientists, and machine learning experts. While you will actively contribute to coding and algorithm development, you will also play a pivotal role in … on: Leading the design and development of advanced Causal AI algorithms, with a focus on time series and tabular data, ensuring they are optimised for scalability and performance. Overseeing feature engineering and machine learning initiatives to deliver robust, production-quality solutions. Providing mentoring and technical guidance to junior engineers and data scientists, fostering a culture of continuous learning … product management, DevOps, and UX/UI design, to seamlessly integrate Causal AI capabilities into our platform's architecture. A minimum of 5 years of experience in machine learning engineering or a related field, with demonstrated success in deploying machine learning models into production environments. Strong academic background in a quantitative discipline (e.g., machine learning, statistics, mathematics) or equivalent More ❯

You have experience optimising solution performance with a constrained set of technologies. You have experience or are keen to engage with productionising machine learning technologies combined with large scale feature engineering. More ❯

You have experience optimising solution performance with a constrained set of technologies. You have experience or are keen to engage with productionising machine learning technologies combined with large scale feature engineering. More ❯

You have experience optimising solution performance with a constrained set of technologies. You have experience or are keen to engage with productionising machine learning technologies combined with large scale feature engineering. More ❯

Job Title: Data Scientist Location: London, UK (Hybrid) Job Type: Permanent Job Description: Experience: Minimum of 8+ years. Skilled Required: LLM, RAG, Finetuning, NLP, Text Summarisation, ML, Feature Engineering Llamaindex, LangChain, LangSmith Vector DB, Vector Search, FAISS Embeddings Experience with OCR, layout models PDF and text file parsing, along with various other file types Experience with REST API More ❯

Job Title: Data Scientist Location: London, UK (Hybrid) Job Type: Permanent Job Description: Experience: Minimum of 8+ years. Skilled Required: LLM, RAG, Finetuning, NLP, Text Summarisation, ML, Feature Engineering Llamaindex, LangChain, LangSmith Vector DB, Vector Search, FAISS Embeddings Experience with OCR, layout models PDF and text file parsing, along with various other file types Experience with REST API More ❯