1 to 25 of 192 scikit-learn Jobs in London

an agile team environment. Self-motivated with a strong desire to learn and adapt. Preferred Qualifications (Nice-to-Have) Basic understanding of machine learning and tools like Scikit-learn , TensorFlow , or PyTorch . Exposure to DevOps practices and CI/CD pipelines . Familiarity with cloud platforms (e.g., AWS , Azure , GCP ). Experience deploying ML models or More ❯

an agile team environment. Self-motivated with a strong desire to learn and adapt. Preferred Qualifications (Nice-to-Have) Basic understanding of machine learning and tools like Scikit-learn , TensorFlow , or PyTorch . Exposure to DevOps practices and CI/CD pipelines . Familiarity with cloud platforms (e.g., AWS , Azure , GCP ). Experience deploying ML models or More ❯

DEPT/AI has a single mission: to make the best work in the industry using AI to enhance everything we do. This role sits within our EMEA Data & AI practice, which has deep expertise in leveraging AI. The team More ❯

ML development and data science - Strong grasp of ML/AI algorithms, including LLMs and automated AI systems - Proficient in Python or R and key frameworks (TensorFlow, PyTorch, scikit-learn) - Skilled in handling large datasets, data wrangling, and statistical modelling - Comfortable working independently on end-to-end ML pipelines - Experienced in visualisation tools (e.g. Matplotlib, Seaborn, Tableau) Desirable More ❯

5+ years of experience in data science, with strong proficiency in writing scale and production-grade code in Python. Solid understanding and proficiency in working with Pandas, NumPy, Scikit-Learn, TensorFlow, and PyTorch, SQL. Proficiency in advanced data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly, Tableau) for creating insightful and interactive visualizations. Solid understanding of data structures 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 ❯

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 ❯

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 ❯

Grow with us. We are looking for a Machine Learning Engineer to work along the end-to-end ML lifecycle, alongside our existing Product & Engineering team. About Trudenty: The Trudenty Trust Network provides personalised consumer fraud risk intelligence for fraud More ❯

as SQL, MongoDB Experience on general programming languages: Python, C++, Java, etc. Experience with deep learning, machine learning and NLP frameworks such as PyTorch (or TensorFlow), HuggingFace Transformer, Scikit-learn Experience with working in Linux A strong intuition for what makes products a joy to use Empathy for how different users will need different things out of a 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 ❯

in real-world applications, especially in NLP or classification problems. Hands on experience with ML tools like TensorFlow, PyTorch etc. Experience with data science libraries such as NLTK, Scikit-learn, SciPy, (Sci)SpaCy etc. Excellent problem-solving and programming skills in Python Excellent communication skills Preferred Qualifications & Skills: If you have the following characteristics, it would be a 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 ❯

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 ❯

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 ❯

and deployment hurdles. Ability to translate business questions into analytical frameworks and interpret results for non-technical stakeholders. Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker. Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention. … social media, and paid media. Excellent problem-solving skills, business acumen, and the ability to translate complex models into actionable insights for non-technical stakeholders. Tools/Frameworks : Scikit-learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy … matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake, Databricks, Redshift, BigQuery) Familiarity with data pipelines and orchestration tools like Airflow Work closely with Data Engineers to ensure model-ready data and More ❯

and deployment hurdles. Ability to translate business questions into analytical frameworks and interpret results for non-technical stakeholders. Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker. Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention. … social media, and paid media. Excellent problem-solving skills, business acumen, and the ability to translate complex models into actionable insights for non-technical stakeholders. Tools/Frameworks : Scikit-learn, XGBoost, LightGBM, StatsModels PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy … matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake, Databricks, Redshift, BigQuery) Familiarity with data pipelines and orchestration tools like Airflow Work closely with Data Engineers to ensure model-ready data and More ❯

experience in a healthcare/life science organization is considered an asset. Other skills we are searching for are: Programming Skills: Proficiency in Python, data analytics, deep learning (Scikit-learn, Pandas, PyTorch, Jupyter, pipelines), and practical knowledge of data tools like Databricks, Ray, Vector Databases, Kubernetes, and workflow scheduling tools such as Apache Airflow, Dagster, and Astronomer. GPU More ❯

Are you a data-driven problem solver with expertise in machine learning and data manipulation? PwC is looking for a Data Scientist to join its innovative team. This role requires hands-on experience with machine learning techniques and proficiency in More ❯

NLP algorithms and techniques and/or experience with Large Language Models (fine tuning, RAG, agents) Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) Have experience productionising machine learning models Are an expert in one of predictive modeling, classification, regression, optimisation or recommendation systems Have experience with Spark Have knowledge of …/or geographical information systems (GIS) Experience with cloud infrastructure Experience with graph technology and/or algorithms Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More information: Enjoy fantastic perks like private More ❯

experiments using A/B testing and statistical analysis to validate approaches Document ML systems and provide support for ongoing performance tuning Use tools like Python, TensorFlow, PyTorch, Scikit-learn, AWS, GCP, MLflow, Docker, SQL , and others Requirements Minimum Bachelors degree in Computer Science, Machine Learning, AI, or a related field Proven experience as a Machine Learning Engineer More ❯

data products through multiple release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts More ❯

data products through multiple release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts More ❯

machine learning PREFERRED QUALIFICATIONS - PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field - 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. - Experience with Deep Learning for search and recommendation systems - Experience More ❯

GenAI pipelines) to our internal AI/ML toolkit Support business-development by shaping analytics in proposals and thought-leadership Tech you'll use (and learn) Python SQL scikitlearn XGBoost TensorFlow/PyTorch LangChain Airflow dbt AWS/GCP/Azure Docker Kubernetes Tableau Streamlit GitHub Actions We're tech agnostic and believe in using the right tool for More ❯