18 of 18 Data Science Engineer Jobs

Data Science Engineer - MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL We are actively working with a global law firm who are actively looking to bolster their IT team as they undergo a global-scale cloud transformation. At present they are looking to take on a new Data Science Engineer (MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) to join their team on a permanent basis. this role we be responsible for the design, development and delivery of advanced analytics and AI solutions. This is a fantastic time to join a top-tier global law firm who have a long … stream of projects in the pipeline alongside a diverse and collaborative team environment. To be considered for this Data Science Engineer (MLOPS, Machine Learning, AI, Artificial Intelligence, Azure, PyTorch, TensorFlow, LangChain, OpenAI, Docker, Kubernetes, GenAI, ETL) role, it's ideal you have: Ideal but not required law firm experience 2-4 years experience within AI/ML More ❯

Data Science Engineer My client is recruiting for a Data Science Engineer to design, develop, and deliver AI and analytics solutions aligned with the organisations Data & AI strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise … experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration skills. Strategic thinking, problem-solving, and stakeholder engagement. More ❯

Data Science Engineer My client is recruiting for a Data Science Engineer to design, develop, and deliver AI and analytics solutions aligned with the organisations Data & AI strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise … experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration skills. Strategic thinking, problem-solving, and stakeholder engagement. More ❯

Data Science Engineer My client is recruiting for a Data Science Engineer to design, develop, and deliver AI and analytics solutions aligned with the organisations Data & AI strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise … experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration skills. Strategic thinking, problem-solving, and stakeholder engagement. More ❯

Data Science Engineer My client is recruiting for a Data Science Engineer to design, develop, and deliver AI and analytics solutions aligned with the organisations Data & AI strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise … experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration skills. Strategic thinking, problem-solving, and stakeholder engagement. More ❯

Data Science Engineer My client is recruiting for a Data Science Engineer to design, develop, and deliver AI and analytics solutions aligned with the organisations Data & AI strategy. Key Responsibilities End-to-end development of AI/ML solutions. MLOps practices: CI/CD, model monitoring, retraining. Use of open-source and enterprise … experience is a plus. AI/ML frameworks: PyTorch, TensorFlow, LangChain. Cloud: Azure (preferred), AWS, GCP. MLOps: CI/CD, model lifecycle, monitoring. Generative AI: LLMs, RAG, chat agents. Data engineering alignment: ETL, governance. Strong coding, communication, and collaboration skills. Strategic thinking, problem-solving, and stakeholder engagement. More ❯

Data Science Engineer My client is recruiting for a Data Science Engineer to design, develop, and deliver AI and analytics solutions aligned with the organisations Data & AI strategy. Key Responsibilities * End-to-end development of AI/ML solutions. * MLOps practices: CI/CD, model monitoring, retraining. * Use of open-source and enterprise … experience is a plus. * AI/ML frameworks: PyTorch, TensorFlow, LangChain. * Cloud: Azure (preferred), AWS, GCP. * MLOps: CI/CD, model lifecycle, monitoring. * Generative AI: LLMs, RAG, chat agents. * Data engineering alignment: ETL, governance. * Strong coding, communication, and collaboration skills. * Strategic thinking, problem-solving, and stakeholder engagement. In accordance with the Employment Agencies and Employment Businesses Regulations 2003, this More ❯

Machine Learning/Data Engineer 700-750/day overall assignment rate to umbrella Fully remote Apply today to join a forward-thinking, tech-driven FTSE 100 organisation using data science and AI to enhance customer experience, optimise supply chains and drive sustainable growth. With 40% of sales from sustainable products, this is a company that … combines scale, innovation and purpose. As a Machine Learning Engineer, youll help maintain the stability and performance of core data and ML systems across Europe. This technical engineering role focuses on reliability, optimisation and critical fixes, ideal if you excel at investigating and debugging complex data flows and ML issues in live production environments. Experience: Proven background … as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep learning algorithms More ❯

Data Science Engineer – Azure | Databricks | AI Innovation Permanent | Birmingham (Hybrid) Amtis is proud to partner with an advanced, data-driven organisation — a business that’s not just talking about AI, but actively building intelligent systems powered by Azure, Databricks, and real-world machine learning applications. This is a hands-on engineering role where you’ll be … at the core of designing, developing, and optimising modern data platforms that enable predictive analytics, AI experimentation, and large-scale automation. You’ll work in an environment where data truly drives business decisions — not just dashboards. If you’re excited by high-volume, high-velocity data challenges and want to work on next-gen infrastructure that supports … advanced analytics and AI workloads, this is your opportunity. What You’ll Be Doing Designing and building scalable, reusable data pipelines using Azure Databricks, Data Factory, and modern cloud tooling Developing secure, flexible data models and optimising performance across massive datasets Collaborating with data scientists to productionise AI models and accelerate experimentation Integrating diverse data More ❯

Machine Learning/Data Engineer £700-750/day overall assignment rate to umbrella Fully remote Apply today to join a forward-thinking, tech-driven FTSE 100 organisation using data science and AI to enhance customer experience, optimise supply chains and drive sustainable growth. With 40% of sales from sustainable products, this is a company … that combines scale, innovation and purpose. As a Machine Learning Engineer, you ll help maintain the stability and performance of core data and ML systems across Europe. This technical engineering role focuses on reliability, optimisation and critical fixes, ideal if you excel at investigating and debugging complex data flows and ML issues in live production environments. Experience … Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Solid understanding of computer science fundamentals and time-series forecasting. Machine Learning: Strong grasp of ML and deep More ❯

articles that define our culture: 1. A Hiring Framework for a New Kind of Services Company 2. The Primacy of Winning Requirements We are seeking AI Engineers with strong data science expertise who are passionate about helping world-leading enterprises put cutting-edge AI agents into production. You’ll work on impactful, high-visibility projects - designing, building, and … delivering intelligent solutions that solve real business problems at scale. What you’ll bring: experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.) critical: Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows. Client-facing experience with a forward-deployed engineering mindset. You’ll work directly … leverage the latest AI technologies. Lead the delivery of high-impact AI products from concept to deployment. You’ll collaborate with top-tier enterprises to design and deploy bespoke data science agents, empowering users to fully leverage the capabilities of our platform. Benefits We care about our people’s lives, both inside and outside of causaLens. Beyond the More ❯

articles that define our culture: 1. A Hiring Framework for a New Kind of Services Company 2. The Primacy of Winning Requirements We are seeking AI Engineers with strong data science expertise who are passionate about helping world-leading enterprises put cutting-edge AI agents into production. You’ll work on impactful, high-visibility projects - designing, building, and … delivering intelligent solutions that solve real business problems at scale. What you’ll bring: experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.) critical: Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows. Client-facing experience with a forward-deployed engineering mindset. You’ll work directly … leverage the latest AI technologies. Lead the delivery of high-impact AI products from concept to deployment. You’ll collaborate with top-tier enterprises to design and deploy bespoke data science agents, empowering users to fully leverage the capabilities of our platform. Benefits We care about our people’s lives, both inside and outside of causaLens. Beyond the More ❯

articles that define our culture: 1. A Hiring Framework for a New Kind of Services Company 2. The Primacy of Winning Requirements We are seeking AI Engineers with strong data science expertise who are passionate about helping world-leading enterprises put cutting-edge AI agents into production. You’ll work on impactful, high-visibility projects - designing, building, and … delivering intelligent solutions that solve real business problems at scale. What you’ll bring: experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.) critical: Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows. Client-facing experience with a forward-deployed engineering mindset. You’ll work directly … leverage the latest AI technologies. Lead the delivery of high-impact AI products from concept to deployment. You’ll collaborate with top-tier enterprises to design and deploy bespoke data science agents, empowering users to fully leverage the capabilities of our platform. Benefits We care about our people’s lives, both inside and outside of causaLens. Beyond the More ❯

articles that define our culture: 1. A Hiring Framework for a New Kind of Services Company 2. The Primacy of Winning Requirements We are seeking AI Engineers with strong data science expertise who are passionate about helping world-leading enterprises put cutting-edge AI agents into production. You’ll work on impactful, high-visibility projects - designing, building, and … delivering intelligent solutions that solve real business problems at scale. What you’ll bring: experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.) critical: Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows. Client-facing experience with a forward-deployed engineering mindset. You’ll work directly … leverage the latest AI technologies. Lead the delivery of high-impact AI products from concept to deployment. You’ll collaborate with top-tier enterprises to design and deploy bespoke data science agents, empowering users to fully leverage the capabilities of our platform. Benefits We care about our people’s lives, both inside and outside of causaLens. Beyond the More ❯

articles that define our culture: 1. A Hiring Framework for a New Kind of Services Company 2. The Primacy of Winning Requirements We are seeking AI Engineers with strong data science expertise who are passionate about helping world-leading enterprises put cutting-edge AI agents into production. You’ll work on impactful, high-visibility projects - designing, building, and … delivering intelligent solutions that solve real business problems at scale. What you’ll bring: experience with traditional data science and machine learning (solid stats, programming, ideally exposure to MLOps, etc.) critical: Hands-on experience building production-grade solutions using LLMs, RAGs, MCPs, and agentic workflows. Client-facing experience with a forward-deployed engineering mindset. You’ll work directly … leverage the latest AI technologies. Lead the delivery of high-impact AI products from concept to deployment. You’ll collaborate with top-tier enterprises to design and deploy bespoke data science agents, empowering users to fully leverage the capabilities of our platform. Benefits We care about our people’s lives, both inside and outside of causaLens. Beyond the More ❯

Senior Data Consultant/Scientist - KPI Dashboarding (Contract)?? Hybrid (Remote + 1 day/week in Heathrow)?? £800/day (Inside IR35)?? Start Date: Week commencing 17th November 2025? Duration: 8 weeks About the RoleA world leading premium airline is launching a new engineering workstream focused on building a KPI dashboard to support transformation initiatives. We're seeking a … Senior Data Consultant/Scientist for a short-term contract to lead the dashboard development and embed it into an existing programme. Key Responsibilities* Design and build KPI dashboards using Power BI or Tableau* Integrate backend data sources (Excel and others) into visual outputs* Define KPIs, identify data sources, scope dashboard requirements, and iterate with stakeholders* Ensure … data quality through modelling, cleaning, and verification* Collaborate with engineering teams to understand operational metrics and reporting needs Required Skills* Expert-level proficiency in SQL, Power BI, and Tableau* Strong experience in data visualisation and dashboarding* Solid understanding of data modelling, data cleaning, and data verification* Ability to work independently and embed into fast-moving More ❯

bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster. Key Responsibilities Collaborate with data and subject matter experts and customer teams to seek, understand, validate, interpret, and correctly use data and business insights Train, validate and deploy machine learning pipelines Test, troubleshoot … backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace. Work Experience Qualification Musts: Experience in data science methods, including statistical analysis , machine learning , and data visualization . Experience identifying and resolving operational or data-related issues using documented procedures and prior case … efficiency. Qualifications Preferred: Applied Machine Learning experience (regression, classification, supervised, and unsupervised learning ) with a strong mathematical foundation in linear algebra , calculus , probability, and statistics. Experience in time-series data analysis , including cleansing and normalization , and experience with scalable Machine Learning ( MapReduce , streaming). Software development expertise in Python and JavaScript , with experience using Git or other version control More ❯

Senior Platform Engineer £Join one of the UK's leading online retailers as they evolve their next-generation data platform. This is an opportunity to shape the backbone of a modern data ecosystem, empowering analysts, ML engineers, and data scientists to deliver smarter, faster insights at scale. You'll play a key role in designing … and engineering platform services that treat data as a core product. This means building scalable, secure, and observable systems that help teams confidently leverage data across the business. You'll work closely with a wide range of technical and non-technical partners to deliver resilient infrastructure, champion data governance, and mentor others in engineering excellence. Shape the … data platform roadmap: Introduce modern observability, quality, and governance frameworks that elevate how teams access and trust data. Develop services, APIs, and data pipelines using modern cloud tooling and automation-first principles. Implement CI/CD pipelines, testing frameworks, and container-based deployments to ensure reliability and repeatability. Collaborate with product engineers, data scientists, and ML practitioners More ❯