26 to 50 of 53 scikit-learn Jobs in London

cloud and MLOps tooling to build scalable, reliable solutions Communicating data-driven insights and influencing both technical and business stakeholders What We’re Looking For Expert-level Python (scikit-learn, pandas, etc.), SQL, and big data platforms (e.g. Databricks) Proven experience with MLOps : deploying, monitoring, and scaling models in production Strong cloud experience (AWS, GCP, or Azure) and More ❯

cloud and MLOps tooling to build scalable, reliable solutions Communicating data-driven insights and influencing both technical and business stakeholders What We’re Looking For Expert-level Python (scikit-learn, pandas, etc.), SQL, and big data platforms (e.g. Databricks) Proven experience with MLOps : deploying, monitoring, and scaling models in production Strong cloud experience (AWS, GCP, or Azure) and More ❯

cloud and MLOps tooling to build scalable, reliable solutions Communicating data-driven insights and influencing both technical and business stakeholders What We’re Looking For Expert-level Python (scikit-learn, pandas, etc.), SQL, and big data platforms (e.g. Databricks) Proven experience with MLOps : deploying, monitoring, and scaling models in production Strong cloud experience (AWS, GCP, or Azure) and More ❯

we do require the ability to become a fluent Python programmer in a short timeframe 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 ❯

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 ❯

learning) and typical software architectures. Experience as a lead developer solving complex problems at scale. Experience mentoring junior engineers. Familiarity with various machine learning frameworks and toolkits (e.g., scikit-learn, XGBoost, TensorFlow). Hands-on experience building GenAI solutions using patterns such as Retrieval-Augmented Generation (RAG) or fine-tuning Large Language Models (LLMs). Greater familiarity with More ❯

managing complex, multi-faceted projects with competing deadlines. Expertise in Agile project management methodologies is a plus. Hands-on experience with a variety of machine learning frameworks (e.g., Scikit-Learn, TensorFlow, PyTorch etc.) and AutoML technologies (e.g., Datarobot, Dataiku). Experience in deploying models at scale using cloud infrastructure is a plus. Skills And Experience At WPP Media More ❯

experience working as a Data Scientist or Machine Learning Engineer in a commercial setting. Strong programming skills in Python, with hands-on experience using libraries such as Pandas, Scikit-Learn, Jupyter, and Matplotlib. Proficient in SQL for data extraction and transformation. Experience with Google Cloud Platform (GCP) and Vertex AI for developing and deploying ML services is highly More ❯

Proven experience in translating technical methods to non-technical stakeholders Strong programming experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain) Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal analysis, surrogate More ❯

deep learning methods and machine learning Experience in building machine learning models for business application Experience in applied research PREFERRED QUALIFICATIONS Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. PhD Amazon is an equal opportunities employer. We believe passionately More ❯

a quantitative field (e.g. Statistics, Mathematics, Physics, Machine Learning) You're confident in Python (production-level) and SQL, and at home with modern ML libraries such as Pandas, scikit-learn, and TensorFlow You have practical experience with MLOps frameworks and deploying models You're skilled at bringing data to life through visualisation, and tools like Tableau feel natural More ❯

insights. What we're looking for: Strong hands-on experience with time-series modelling (ARIMA, VAR, GARCH, Prophet, LSTMs, Transformers, etc.). Proficiency in the Python ecosystem (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow; polars/dask a plus). Familiarity with SQL and handling large datasets. Curiosity and interest in financial markets and macroeconomics . Master's More ❯

to grow and learn on the job. You would have experience with some of the following technologies and areas: Python and ML/NLP frameworks such as scikit-learn, TensorFlow, or PyTorch Large/Small Language Models (LLMs/SLMs) and libraries like Hugging Face Transformers Prompt engineering for tasks like summarization, Q&A, or information extraction More ❯

to stochastic optimisation models. What skills, experience and qualities are we looking for? Python - demonstrable experience required Experience working across a range of ML models, e.g. TensorFlow and scikit-learn Significant experience in the energy industry, with a specific focus on forecasting the short-term power markets GitHub or Azure DevOps knowledge is desired SQL knowledge is desired More ❯

operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If you’re More ❯

operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If you’re More ❯

a commercial or trading environment Proficiency in time series analysis, regression modelling, and forecasting techniques Strong experience with Python and core libraries for data science (e.g., pandas, NumPy, scikit-learn, statsmodels) Ability to manipulate and analyse large, complex datasets with attention to detail Clear, confident communicator who can explain analytics and influence commercial decisions Experience using visualisation tools More ❯

develop and deliver ML-powered solutions: Model Development : Assist in building and training machine learning and deep learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models Feature Engineering : Support the design and selection of relevant input features to … graduate (or soon-to-be) in Computer Science, Data Science, Engineering, Mathematics, Statistics, Physics, or a related discipline Proficiency in Python and familiarity with ML libraries such as Scikit-learn, TensorFlow, or PyTorch Strong understanding of basic machine learning concepts and algorithms (e.g. regression, classification, decision trees) Good grasp of data structures, algorithms, and programming fundamentals. Analytical mindset More ❯

Cloud). Strong analytical mindset with the ability to translate complex data insights into clear business impact. Working knowledge of machine learning and advanced analytics (e.g., TensorFlow, PyTorch, Scikit-learn). Exceptional stakeholder management skills, comfortable engaging with C-suite executives and senior investors. Strong knowledge of data governance and compliance frameworks (GDPR, CCPA). Thrive in fast More ❯

Cloud). Strong analytical mindset with the ability to translate complex data insights into clear business impact. Working knowledge of machine learning and advanced analytics (e.g., TensorFlow, PyTorch, Scikit-learn). Exceptional stakeholder management skills, comfortable engaging with C-suite executives and senior investors. Strong knowledge of data governance and compliance frameworks (GDPR, CCPA). Thrive in fast More ❯

enhanced DV clearance (mandatory) Proven experience in a data science or machine learning role Strong programming skills in Python and familiarity with key data libraries (e.g. pandas, NumPy, scikit-learn) Experience with data wrangling , feature engineering, and model optimisation Understanding of data pipelines , APIs, and production deployment workflows Excellent communication skills and a collaborative approach Why Apply? Work More ❯

dashboarding software such as Power BI or Tableau is important. Familiarity with programming languages such as Python or R and their associated data analysis libraries (e.g., NumPy, Pandas, scikit-learn) is a plus. Statistical Expertise: Strong understanding of statistics, including descriptive statistics, regression, probability, sampling, and hypothesis testing. Communication: Excellent written and verbal presentation skills, with the ability More ❯

ML/AI (or equivalent practical experience through academic projects or early career roles) You're comfortable coding in Python and using ML frameworks (e.g. PyTorch, Hugging Face, scikit-learn) You've worked with large language models (LLMs) - not just calling APIs, but experimenting with different ways to get the best out of them: Prompt engineering (designing effective More ❯

models powering AI agents and intelligent systems. Innovate in NLP, generative AI, and MLOps to deliver robust, scalable AI solutions. Key Responsibilities : Develop ML models using libraries like Scikit-learn, Hugging Face, and LangChain. Lead model training, tuning, and deployment activities. Implement MLOps pipelines enabling continuous integration/delivery of ML models. Collaborate with cross-functional teams for More ❯

technology across the business. Machine Learning Engineer, key skills: Significant experience working as a Machine Learning Engineer Solid knowledge of SQLandPython's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib). GCP, VertexAI experience is desirable (developing GCP machine learning services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software More ❯