1 to 25 of 43 scikit-learn Jobs in Central London

At Peregrine, were constantly seeking Specialist Talent that offer the ideal mix of skills, experience, and attitude, to place with our vast array of clients. From Project Change Professionals in large government organisations to Software Developers in the private sector More ❯

regulations. Technical Skills required: Programming: Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with cloud platforms such as AWS More ❯

us again, and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong communication More ❯

Python or similar programming (intermediate level). Expertise in NLP libraries such as spaCy, Transformers, Sentence Transformers, LangChain, LangGraph, LlamaIndex, BERTopic. Hands-on experience with machine learning libraries (scikit-learn, TensorFlow, PyTorch). Experience with cloud platforms (AWS, Google Cloud, Azure) and version control systems (Git). Knowledge of SQL and database management. NLP Competencies : Strong understanding of More ❯

someone who is technically proficient, solution-oriented, strategically minded, and capable of communicating insights clearly to both technical and non-technical audiences. Requirements Advanced Python skills (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) & SQL (Snowflake a plus) Experience with Data warehousing and database technologies Solid experience in machine learning (modeling to deployment) Cloud exposure (GCP/AWS/Azure More ❯

ability to lead end-to-end AI projects—from data exploration and model development to deployment and evaluation. Expert-level proficiency in Python and ML libraries such as Scikit-learn, XGBoost, TensorFlow, PyTorch, and/or Hugging Face. Experience working with large-scale datasets, cloud platforms (AWS/GCP), and ML Ops tools is a plus. Excellent communication More ❯

AWS services such as Lambda, DynamoDB, S3, SNS, SQS, and Serverless EMR Experience with SQL and NoSQL databases Hands-on Python experience, particularly with data libraries (e.g., pandas, scikit-learn) Familiarity with RESTful APIs and event-driven architectures Strong debugging, system design, and testing skills (e.g., JUnit) Passion for building scalable, reliable platforms supporting real-world use cases More ❯

SKILLS AND EXPERIENCE 5–7 years of experience in a consumer credit environment, particularly in decision science or data science. Strong technical skills in Python (including libraries like scikit-learn, XGBoost, LightGBM). Experience working with transactional data and credit bureau sources. Familiarity with model monitoring and performance tracking frameworks. Proficient SQL skills for querying and data transformation. More ❯

regulations. Technical Skills required: Programming: Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with cloud platforms such as AWS 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 ❯

including frameworks like Hugging Face, LangChain, or custom pipelines. Deep technical understanding of biometric security systems and privacy-aware architecture. Strong Python/ML stack (e.g., PyTorch, TensorFlow, Scikit-learn). Experience building real-time AI systems in production environments . Exposure to Agentic AI concepts or multi-agent systems is a strong plus. Due to the high More ❯

Master’s degree from a Russell Group university in Data Science, Computer Science, Mathematics, Physics, Engineering, or a related discipline Strong programming skills in Python (e.g. NumPy, pandas, scikit-learn, matplotlib); R is also welcome A solid understanding of core machine learning concepts, data wrangling, and model evaluation Proficiency with SQL and experience handling large datasets A passion More ❯

in a quantitative field. • Proven experience of large-scale data analysis and hypothesis testing. • Strong proficiency in statistical analysis and predictive modeling. • Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. • Excellent problem-solving skills and attention to detail. • Strong communication skills with the ability to present complex data insights to More ❯

as preferred bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. Terraform). Technology deployment– proven experience usinPg 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 ❯

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 ❯

into production. Your Profile: Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong understanding of SQL More ❯

in a quantitative field. Proven experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with the ability to present complex data insights to More ❯

or a related field. Experience or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI innovation and a desire to More ❯

REQUIREMENTS: 4+ years of experience in machine learning engineering, with a strong focus on productionizing ML models and MLOps. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows More ❯

grow and shape the data science team and its role within the wider business. What We’re Looking For Strong technical foundation with proficiency in Python (Pandas, NumPy, Scikit-learn), SQL, and cloud platforms (GCP or AWS). Experience with modern data warehouses (BigQuery, Snowflake, Redshift). Proven experience in deploying machine learning models or optimisation algorithms into More ❯

background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

or AI domains Proven track record of leading complex AI projects in an agile environment Strong technical proficiency with modern ML tools and frameworks: PyTorch, TensorFlow, SparkMLLib, SciPy, Scikit-Learn, NLTK (etc) MLflow or similar ML lifecycle tools Cloud platforms (AWS/Azure/GCP) Experience with AI governance and responsible AI practices Understanding of public sector data More ❯

depth knowledge of how they work. Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn . DevOps: You have experience working with DevOps tooling, such as Kubernetes, Terraform, CI/CD tools and Docker. Cloud: You have worked with cloud-based environments before More ❯

🚀 We’re Hiring: Data Scientist | Leading Music Investment Company | London (Hybrid) Are you a data expert who loves solving real-world problems with predictive models and analytics? Join a leading music rights investment and management company where your models will More ❯