1 to 25 of 188 Permanent Machine Learning Jobs in Central London

possesses practical expertise in machine learning, with experience across the full lifecyclefrom business scoping and data engineering through to deployment, monitoring, and ethical considerations. Familiar with classical ML techniques (e.g., regression, classification, clustering), as well as deep learning, NLP, transfer learning, and recent advancements in LLMs and generative AI. Able to contextualise these techniques in industry … settings, such as financial forecasting, operations optimisation, or customer segmentation. Comfortable with key ML frameworks (such as Scikit-learn, TensorFlow, PyTorch, Hugging Face) and data manipulation tools (Pandas, NumPy), as well as version control, containerisation, and ML deployment pipelines. Understands how to apply MLOps principles in production environments To be successful in this role you must have hands-on experience … designing and deploying ML models in industryideally within agile or cross-functional teams. Understands what it takes to build and maintain scalable, ethical, and production-ready AI systems. Can share personal stories of both success and failure in deploying ML, helping learners understand real-world challenges like stakeholder alignment, data quality, model drift, or technical debt in pipelines. Ideally, has More ❯

Data Lake & Storage: Databricks Delta Lake, Amazon S3 Data Transformation: dbt Cloud Data Warehouse: Snowflake Analytics & Reporting: Power BI, Excel, Snowflake SQL REST API Advanced Analytics: Databricks (AI & Machine Learning) Governance & Infrastructure: Centralised Data Catalogue & Access Control (Okta) Job Scheduling & Monitoring (AWS, Splunk) Agile Data Engineering with centralised code repositories BI Data Portal: Power BI However this coexists More ❯

onsite) - Flexible Salary: £45,000 DOE + Benefits Our Data Analytics business continues to grow and we are now looking for an experienced and technical Machine Learning (ML) Engineer to join one our offices with hybrid or remote UK working. This is an exciting role and would most likely suit someone with previous experience in a similar role … where they have gained knowledge and experience of designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. You must have good technical knowledge of Phyton, SQL, CI/CD and familiar with Power BI. A FTSE 250 company, they combine expertise and insight with advanced technology and analytics to address … the analytics team and non-technical stakeholders. Your profile Essential Criteria Previous experience in designing, building, optimising, deploying and managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting More ❯

helping global brands design and deploy intelligent systems that solve real business problems. They combine deep engineering know-how with domain expertise to build the data infrastructure that powers machine learning and generative AI at scale. 🔍 About the Role As a Lead Data Engineer , you’ll play a critical role in delivering AI-driven solutions for clients—owning … ensure clean, accessible, and production-grade data pipelines are in place to support experimentation and deployment. 🛠️ Key Responsibilities Build and maintain high-performance data pipelines to power AI/ML use cases Architect cloud-native data platforms using tools like Databricks , Airflow , Snowflake , and Spark Collaborate with AI/ML teams to align data processing with model requirements Develop ETL … GDPR , RBAC) Mentor junior engineers and guide technical decisions on client engagements ✅ Ideal Experience Strong in Python and SQL , plus familiarity with Scala or Java Experience supporting AI/ML workflows and working with Data Scientists Exposure to cloud platforms: AWS , Azure , or GCP Hands-on with modern data tooling: Spark , Databricks , Snowflake , Airflow Solid grasp of data modelling, orchestration More ❯

About the Opportunity: We are seeking an ambitious and intellectually curious Junior Data Scientist to join a fast-growing, forward-thinking team working at the forefront of data science, machine learning, and applied AI. This is an excellent opportunity for a recent Master’s graduate eager to apply their academic expertise to solving real-world challenges—whether it … s predicting customer behaviour, optimising operations, or identifying patterns in complex datasets. You’ll collaborate with experienced data scientists, machine learning engineers, and subject-matter experts to design, develop, and deploy models that deliver meaningful impact across a variety of industries. What You’ll Be Doing: Designing and building machine learning models to solve real-world … B testing Presenting findings clearly to both technical and non-technical stakeholders Collaborating across data science, engineering, and product teams to build scalable solutions Staying current with advancements in machine learning and AI, and contributing new ideas to internal R&D discussions What We’re Looking For: A recently completed Master’s degree from a Russell Group university More ❯

solutions that make a difference from day one! In this role, you’ll work alongside experienced data scientists, engineers, and business stakeholders to design, build, and deploy analytics and machine learning solutions. You’ll apply your analytical mindset and technical skills to unlock insights, drive decision-making, and support products used by thousands every day. Whether you're … company that values data at its core. What’s in it for you? 📊 Meaningful Work : Work on real data challenges across forecasting, customer analytics, risk modelling, and business intelligence. 📈 Learning & Development : Structured support including mentoring, online courses, internal workshops, and the chance to explore the latest tools in data science. 💡 Culture of Innovation : Be part of a collaborative and … and performance-based bonuses. We’re looking for someone who has: 🎓 A degree in Data Science, Mathematics, Computer Science, Statistics, or a related field. 🧠 Solid understanding of data analysis, machine learning concepts, and statistical methods. 🐍 Proficiency in Python (e.g., Pandas, Scikit-learn, NumPy) or R, with exposure to tools like Jupyter, SQL, or cloud platforms (e.g., AWS, GCP More ❯

clearly to all audiences. Mentor junior team members and support capability growth. Work with engineers to productionise solutions. What we’re looking for: Strong knowledge of regression, classification, and machine learning algorithms, with experience applying them in real-world settings Passion for sports analytics, with previous working experience an advantage Proficient in Python or R, with good SQL More ❯

and visualisation Communicate insights clearly to all audiences Mentor junior team members and support capability growth Work with engineers to productionise solutions Requirements: Strong knowledge of regression, classification, and machine learning algorithms, with experience applying them in real-world settings Passion for sports analytics, with previous working experience an advantage Proficient in Python or R, with good SQL More ❯

Lead/Senior Machine Learning Engineer £110,000-£120,000 Bonus up to 10% Shares so as they continue to grow you benefit to Hybrid working - one day a week London (with door always open policy) Are you a innovative, decisive Machine Learning Engineer looking for your next challenge? This is your chance to join a … deployment times, increasing scalability, and improving model performance through regular updates and monitoring. You will work closely with the Data Scientists and Product team to deliver scalable, production-grade ML systems. This is a super exciting time to join the business who after a number of years of great success have hit profitability and now want to grow through strategic … and non-technical stakeholders through clear storytelling Required Skills Education: Bachelor’s or Master’s degree in Statistics, Data Science, Computer Science or related field Experience: Proven experience in ML model lifecycle management ● Core Competencies: Model lifecycle: You’ve got hands-on experience with managing the ML model lifecycle, including both online and batch processes Statistical Methodology: You have worked More ❯

security Collaborate with business analysts, data scientists, and stakeholders across underwriting, finance, and ops Contribute to solution design, development assurance, and platform evolution Support delivery of data models, APIs, ML integrations, and reporting tools Key Skills: Hands on experience designing and delivering solutions using Azure services including Azure Data Factory, Azure Databricks, Azure Synapse, Azure Storage, Azure DevOps. Proven track More ❯

provide deep customer insights, predict behaviour, and enable hyper-targeted marketing. Responsibilities: Lead the organization’s data science initiatives, developing advanced analytics strategies, and driving innovation through AI and machine learning Develop and implement the company’s data science strategy to drive business growth. Stay ahead of emerging trends in … data science, AI, and big data technologies. Challenge the status quo and always look for ways to improve data science Oversee the development, deployment, and optimisation of AI/ML models. Partner with business leaders to identify key challenges and opportunities. Requirements: PhD or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field Proven leadership … a data science or AI-driven organization. Proficient in Python (core skill), with strong experience in SQL, AWS, and CI/CD pipelines Strong technical expertise in AI/ML and advanced analytics. Excellent problem-solving, communication, and stakeholder management skills. Strategic vision and business acumen. **Please note that this role does not offer visa sponsorship** How to Apply: Register More ❯

and Data science programme to drive high impact data science outcomes. Promote excellence and innovation in data science methods for measuring the quality of health and social care services, learning from best practice (national/international), both internally and externally. Assess the effectiveness of different advanced statistical and data science modelling approaches and advise data scientists on best tools … inclusion strategy. Skills and Experience Post-graduate qualification in relevant subject or has equivalent professional experience. In-depth understanding of a wide range of data science techniques, such as machine learning and natural language processing, and able to apply them to a variety of analytic problems. Previous experience in delivery of complex, advanced analytics and/or data … of data science tools, especially Python, R, and SQL Experience of cloud computing - Cloud Computing – Azure, AWS or GCP Substantial experience working in cloud-based tools like Databricks for Machine Learning, Azure Machine Learning and Azure AI Foundry as well as experience helping others to use them. If you are seeking a Data Science leadership role More ❯

and Data science programme to drive high impact data science outcomes. Promote excellence and innovation in data science methods for measuring the quality of health and social care services, learning from best practice (national/international), both internally and externally. Assess the effectiveness of different advanced statistical and data science modelling approaches and advise data scientists on best tools … inclusion strategy. Skills and Experience Post-graduate qualification in relevant subject or has equivalent professional experience. In-depth understanding of a wide range of data science techniques, such as machine learning and natural language processing, and able to apply them to a variety of analytic problems. Previous experience in delivery of complex, advanced analytics and/or data … of data science tools, especially Python, R, and SQL Experience of cloud computing - Cloud Computing – Azure, AWS or GCP Substantial experience working in cloud-based tools like Databricks for Machine Learning, Azure Machine Learning and Azure AI Foundry as well as experience helping others to use them. If you are seeking a Data Science leadership role More ❯

system support, monitoring & troubleshooting. Experience of working in environments with high information security standards to meet needs of ISO27001, SOC2 and GDPR etc Experience with AI and/or Machine Learning Project planning and management experience. Experience with finance systems i.e. Sage, Qube, IRIS or similar. Experience with CRMs such as HubSpot or similar. More ❯

future reporting needs in collaboration with business units. Engage with stakeholders to ensure reporting solutions align with business goals. Apply Agile project management principles to deliver iterative improvements. Support ML metadata extraction and integration into reporting workflows. Use scripting languages (e.g., DAX, M, Python, PowerShell) to support data transformation and automation. Qualifications Minimum 3 years of industry experience in a … Agile methodologies and tools (e.g., Jira, Azure DevOps). Excellent communication and stakeholder management skills. Ability to work both independently and collaboratively in a hybrid work environment. Experience with ML metadata extraction and scripting languages is a plus. Experience in the procurement or supply chain industry is a nice to have. Bachelor's degree in Computer Science, Information Systems, or More ❯

Semantic Kernel , or Azure OpenAI . Appreciation for ethical AI considerations including data privacy , security , and bias mitigation . Eagerness to explore emerging technologies and collaborate with AI/ML teams to bring intelligence into real-world business workflows. How we’d like you to lead: Advantage Zensar We are a technology consulting and services company with 11, 800+ associates More ❯

the entire delivery lifecycle—from design and development to testing, deployment, and ongoing support. You will work across the full machine learning workflow, applying advanced analytics and ML techniques to extract structured insights from complex insurance submission documents, conduct exposure analytics, and model asset behaviour for the commercial insurance market. Responsibilities Design, build, and deploy machine learning … in version control, testing, CI/CD, and MLOps Share expertise through peer code reviews, documentation, and collaborative learning initiatives Stay current with emerging trends in AI/ML, particularly in areas such as LLMs, NLP, and intelligent document automation What skills and experience will I need to bring with me? You’ll need to be able to demonstrate … all the skills, you have a passion and willingness for learning. Here’s what the teams will be looking for: 3–5 years of professional experience in data science ML, or applied AI role Strong problem-solving and analytical skills with the ability to approach complex technical challenges independently Proven experience in building, deploying, and maintaining ML models in production More ❯

Scientist to drive the development and integration of advanced machine learning tools into scalable healthcare solutions. You will collaborate with engineering and research teams to design robust ML workflows, improve infrastructure, and ensure production-grade deployment of AI systems. This is an ideal role for someone passionate about using technology to solve real-world healthcare challenges. Key Responsibilities … Research and prototype innovative AI technologies aimed at improving system performance and clinical efficiency Enhance ML development workflows with tools for model tracking, experiment management, and reproducibility Apply data science techniques to extract insights from complex and varied data sets Plan and manage infrastructure for model training and deployment Develop systems for monitoring ML models in production environments Build and … Requirements: Degree in Computer Science, Software Engineering, or a related technical discipline Minimum 5 years of industry experience or a PhD in a relevant area Strong theoretical foundation in ML, deep learning, and computer vision Proficient in Python and common ML frameworks such as PyTorch Hands-on experience with MLOps platforms and tools (experience with ClearML is beneficial) Familiarity More ❯

help brands across entertainment, tech, sports, and consumer goods maximise their marketing impact. You’ll be part of a collaborative Data Science team, working on large-scale datasets, building machine learning models, and delivering actionable insights for high-profile clients. Key Responsibilities Lead the development of … solutions for complex client challenges, defining clear 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 … statistical and machine learning expertise, with the ability to apply and evaluate various algorithms. Proficiency in Python (Pandas), SQL, and data analytics tools. Experience deploying and evaluating ML models in production environments. Ability to interpret complex datasets, drawing meaningful insights to drive business decisions. Strong communication skills, with experience in managing client relationships. A degree in a relevant More ❯

partners directly with portfolio companies to drive measurable operational and financial performance—powered by data. They’re now hiring a Principal Data Scientist to lead high-impact analytics and machine learning projects across a wide variety of real-world domains - from manufacturing to customer experience and commercial optimisation. Working closely with a multidisciplinary team, you’ll have the … problems into measurable data 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 … design choices Communicate findings and strategic insights to both technical and non-technical stakeholders About You You’re an experienced data scientist with a proven track record of using machine learning to solve real-world business challenges. You’re just as comfortable in Python as you are in a boardroom, and you’re motivated by measurable impact, not More ❯

A specialist data consultancy is seeking a Senior Data Scientist with strong hands-on experience in Machine Learning and Generative AI. This role offers the opportunity to work on high-impact projects across various industries, applying advanced data techniques to solve real-world … business problems. This is an excellent opportunity to join a collaborative team delivering innovative AI and data science solutions for a diverse client base. Role Responsibilities Design and implement ML and Generative AI models to address client challenges Work closely with data engineers and MLOps professionals to deliver production-ready systems Apply techniques such as large language models (LLMs), retrieval … data science and bring fresh ideas to internal and external projects Support a collaborative team culture through knowledge sharing and technical discussions Skills and experience required Proven experience delivering ML and/or Generative AI projects from concept to deployment Hands-on experience with frameworks such as Hugging Face, LangChain, and open-source LLMs Familiarity with tools such as Databricks More ❯

a new Senior Data Scientist to join the team. You'll be working at the intersection of data, technology, and marketing, you’ll lead the delivery of cutting-edge machine learning, optimisation, and analytics solutions that drive measurable business outcomes. Reporting directly to the Director of Data, you’ll take ownership of high-impact projects across areas such … data science solutions across predictive modelling, optimisation, and experimentation. Act as a strategic data partner to key clients, owning technical delivery and ensuring high-quality results. Design and deploy machine learning models and optimisation algorithms in production environments. Collaborate with engineering, marketing, and analytics teams to integrate data science into campaign strategy and tooling. What We’re Looking … For Strong technical foundation with proficiency in Python, SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses. Proven experience in deploying machine learning models or optimisation algorithms into production. Solid understanding of digital marketing concepts, platforms (e.g., Google Ads, Meta), and analytics tools. Demonstrated experience across key use cases such as: Customer Lifetime Value More ❯

this expansion, they’re looking for an experienced Data Scientist to join their fast-paced, agile environment on a 6-month hybrid contract . Key Responsibilities: Design and deploy machine learning models for risk scoring, customer segmentation, and product optimisation Analyse large financial datasets to uncover trends and support product and credit teams Develop custom statistical models for … teams Contribute to scalable data pipeline and feature store development Requirements: 3+ years of experience as a Data Scientist in a commercial setting Strong skills in Python, SQL , and machine learning libraries (e.g., scikit-learn, XGBoost, etc.) Familiarity with cloud platforms (e.g., AWS, GCP) and version control (e.g., Git) Experience working with financial or transactional data is a More ❯

Responsibilities: Analyse complex datasets: Work with large volumes of financial data to identify trends, patterns, and insights that drive strategic decisions. Support predictive modeling: Collaborate on the development of machine learning models to forecast financial outcomes and optimise business processes. Develop data-driven solutions: Create algorithms and tools that automate and enhance decision-making across the company. Collaborate … Preferred disciplines include Statistics, Mathematics, Computer Science, Engineering, or related fields. Proficiency in programming languages: Experience with Python and SQL for data analysis, manipulation, and modeling. Basic understanding of machine learning: Familiarity with predictive modeling techniques and algorithms, in particular NLP, LLM's and Time Series Forecasting. Experience with data visualisation tools: Knowledge of tools like Tableau/… A Bonus If You Have: Experience in finance: Prior exposure to financial data or working in a financial services environment is a plus. Curiosity and drive: A passion for learning and staying updated with the latest trends in data science and finance. Problem-solving mindset: Ability to think critically and approach challenges with innovative solutions. The Benefits: Growth opportunities More ❯

About the Role As a Senior Data Scientist, you’ll take ownership across the full lifecycle of model development —from data wrangling and feature engineering to building and deploying ML models in production. Your work will directly power business decisions across underwriting, fraud detection, and customer conversion . This is a hands-on, end-to-end role where your skills … a Bachelor’s degree in Computer Science, Mathematics, Statistics, or related field Brings advanced SQL skills and strong experience with Python (pandas, sklearn, seaborn, etc.) Understands the mechanics behind ML algorithms—not just how to run them Enjoys solving problems and improving processes Has hands-on experience developing underwriting or behavioural credit models - Expect to be using your skills to … key aspect of the role — Be ready to bring your team's ideas to life! It’s a plus if you also have: A Master’s in Data Science, ML, or a related field Credit card industry knowledge Experience with deep learning (Keras, TensorFlow) Familiarity with GitHub or Bitbucket Tableau experience or similar An interest in applying research to More ❯