City of London, London, United Kingdom Hybrid / WFH Options
SLB
Job Title: HR Data Science Intern About Us: We are a global technology company, driving energy innovation for a balanced planet. At SLB we create amazing technology that unlocks access to energy for the benefit of all. We are facing More ❯
Job Title: HR Data Science Intern About Us: We are a global technology company, driving energy innovation for a balanced planet. At SLB we create amazing technology that unlocks access to energy for the benefit of all. We are facing More ❯
versa. Proven experience of change management skills. Core technical skills: Strong knowledge of data science fundamentals (Machine Learning methods, Statistics). Fluent in common analytics tools (Python, Pandas, Numpy, ScikitLearn, SQL, etc.) Comfortable to use data visualization libraries (e.g. Seaborn, Matplotlib) Demonstrated initiative, judgment and discretion while handling sensitive information Preferred Qualifications: If you have the following characteristics, it would More ❯
Job Description Job Role : Data & AI Consultant - R&D Location: London/Manchester/Edinburgh Career Level : Consultant Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations More ❯
We are looking for a Senior Data Scientist who enjoys seeing their work used as part of 'real-life' solutions. Not only will your work directly contribute to our client deliverables, but you will have the opportunity to see the More ❯
We are looking for a Senior Data Scientist whoenjoys seeing their work used as part of 'real-life' solutions. Not only will your work directly contribute to our client deliverables, but you will have the opportunity to see the process More ❯
Crawley, Sussex, United Kingdom Hybrid / WFH Options
Rentokil Initial Group
The AI Engineer is a key role in the Data Platform Portfolio team, building the data platform, driving value from data across the business. With strong technical skills and business acumen to help turn millions of potential data points into More ❯
We are looking for a Data Scientist to help the Applied AI team in the Bank, holding expertise in machine learning and AI capabilities, working on ML/AI model development, evaluation and deployment based on large-scale data processing. More ❯
We are looking for a Data Scientist to help the Applied AI team in the Bank, holding expertise in machine learning and AI capabilities, working on ML/AI model development, evaluation and deployment based on large-scale data processing. More ❯
Senior Data Scientist - Consumer Lending Hybrid working - London Offices Negotiable to £75,000 DEO + Benefits Reference - J12979 Our client is an innovative UK based consumer finance business, with a digital credit card launched in 2018, and a pipeline of More ❯
previous management or mentorship. Have good communication skills. Nice to have Experience deploying LLMs and agent-based systems Our technology stack Python and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc. MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow Monitoring: New Relic CI/ More ❯
degree in machine learning, computer science, engineering, or a related discipline, with a BSc required and an MSc considered advantageous. Experienced in using machine learning frameworks such as Scikit-learn, Keras, and PyTorch, with additional familiarity with MLFlow and AzureML seen as a positive. Have working knowledge of CI/CD practices, ML Ops, ML pipelines, automated testing More ❯
data science or data engineering solutions into production. You're comfortable writing production-grade code, not just notebooks. Strong Python and SQL skills, including the basic libraries (Pandas, Numpy, ScikitLearn). You value writing clean, maintainable, and tested code. Proven ability to design, build, and maintain data pipelines and tools from scratch that are reliable, maintainable, and scalable. Strong communicator More ❯
🔥 Who We Are At Ultralytics, we relentlessly drive innovation in AI, building the world's leading YOLO models. We're looking for passionate individuals obsessed with AI, eager to make a global impact, and ready to excel in a dynamic More ❯
🔥 Who We Are At Ultralytics, we relentlessly drive innovation in AI, building the world's leading YOLO models. We're looking for passionate individuals obsessed with AI, eager to make a global impact, and ready to excel in a dynamic More ❯
Date: July 2025 Company: Fuzzy Labs Job Title: MLOps Engineer Location: Central Manchester Working style: Hybrid Fuzzy Labs are a Manchester based startup that helps our clients productionise machine learning through Open Source MLOps. We exist to help harness and More ❯
Date: July 2025 Company: Fuzzy Labs Job Title: Lead MLOps Engineer Location: Central Manchester Working style: Hybrid Fuzzy Labs are a Manchester based startup that helps our clients productionise machine learning through Open Source MLOps. We exist to help harness More ❯
Title: Full Stack Developer Reports to : Engineering Manager Location: London (Hybrid, 2 days office based per week) Type: Full-Time, Permanent Salary: £40,000-£54,000 + Benefits + EMI options Candidates must be eligible for Security Clearance Join Our More ❯
quality and spend; implement automated retraining triggers. Collaboration - work with Data Engineering, Product and Ops teams to translate business constraints into mathematical formulations. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you'll … recommender work at production scale (dynamic pricing, yield, marketplace matching). Mathematical optimisation know-how - LP/MIP, heuristics, constraint tuning, objective-function design. Python toolbox: pandas, NumPy, scikit-learn, PyTorch/TensorFlow; clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for heavy More ❯
a model as a container, update an Airflow (or Azure Data Factory) job. Review: inspect dashboards, compare control vs. treatment, plan next experiment. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you'll … recommender work at production scale (dynamic pricing, yield, marketplace matching). Mathematical optimisation know-how - LP/MIP, heuristics, constraint tuning, objective-function design. Python toolbox: pandas, NumPy, scikit-learn, PyTorch/TensorFlow; clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for heavy More ❯
is not only technically strong, but solution-oriented, strategically minded, and able to communicate insights clearly to both technical and non-technical audiences. Requirements: Advance Python (Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch) & SQL skills. (Snowflake a plus) Experience with Data warehousing and database technologies Solid machine learning experience (modelling to deployment) Cloud exposure (GCP/AWS/ More ❯
Strong python programming skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯
Strong python programming skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯
Strong python programming skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯
Strong python programming skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of More ❯