176 to 200 of 222 scikit-learn Jobs in London

key is that you will be deeply involved with productionising and deploying. Strong Python, SQL and programming skills Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWSs machine learning infrastructure. Again this is a superb More ❯

statistics and data science in a commercial setting. Proven track record in customer or marketing analytics - understanding acquisition, engagement, churn, and lifetime value. Proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels) for data wrangling, analysis, and modelling. Ability to communicate complex findings in a clear, business-relevant way. Experience working collaboratively in agile, cross-functional teams. Please note More ❯

statistics and data science in a commercial setting. Proven track record in customer or marketing analytics - understanding acquisition, engagement, churn, and lifetime value. Proficiency in Python (Pandas, NumPy, Scikit-learn, Statsmodels) for data wrangling, analysis, and modelling. Ability to communicate complex findings in a clear, business-relevant way. Experience working collaboratively in agile, cross-functional teams. Please note More ❯

internship or full-time) in data science or climate risk modelling Strong grasp of statistical modelling and machine learning techniques Proficiency in Python and common ML libraries (e.g. scikit-learn) Curious, pragmatic, and driven to solve real-world problems with high social impact Passionate about the intersection of data science, insurance, and climate resilience If this role interests More ❯

internship or full-time) in data science or climate risk modelling Strong grasp of statistical modelling and machine learning techniques Proficiency in Python and common ML libraries (e.g. scikit-learn) Curious, pragmatic, and driven to solve real-world problems with high social impact Passionate about the intersection of data science, insurance, and climate resilience If this role interests More ❯

internship or full-time) in data science or climate risk modelling Strong grasp of statistical modelling and machine learning techniques Proficiency in Python and common ML libraries (e.g. scikit-learn) Curious, pragmatic, and driven to solve real-world problems with high social impact Passionate about the intersection of data science, insurance, and climate resilience If this role interests More ❯

internship or full-time) in data science or climate risk modelling Strong grasp of statistical modelling and machine learning techniques Proficiency in Python and common ML libraries (e.g. scikit-learn) Curious, pragmatic, and driven to solve real-world problems with high social impact Passionate about the intersection of data science, insurance, and climate resilience If this role interests More ❯

want people to have a major say and influence on projects. Technical Skills: Python - strong knowledge required Experience working across a range of ML models, e.g. TensorFlow and scikit-learn Commercial experience working on short-term forecasting markets, across either energy, power or financial markets. GitHub or Azure DevOps knowledge is desired SQL knowledge is desired The successful More ❯

want people to have a major say and influence on projects. Technical Skills: Python - strong knowledge required Experience working across a range of ML models, e.g. TensorFlow and scikit-learn Commercial experience working on short-term forecasting markets, across either energy, power or financial markets. GitHub or Azure DevOps knowledge is desired SQL knowledge is desired The successful More ❯

want people to have a major say and influence on projects. Technical Skills: Python - strong knowledge required Experience working across a range of ML models, e.g. TensorFlow and scikit-learn Commercial experience working on short-term forecasting markets, across either energy, power or financial markets. GitHub or Azure DevOps knowledge is desired SQL knowledge is desired The successful More ❯

want people to have a major say and influence on projects. Technical Skills: Python - strong knowledge required Experience working across a range of ML models, e.g. TensorFlow and scikit-learn Commercial experience working on short-term forecasting markets, across either energy, power or financial markets. GitHub or Azure DevOps knowledge is desired SQL knowledge is desired The successful More ❯

drives user clicks- A functional internal tool for non-technical stakeholders- Documentation and guidance for productionisation Required Skills Must-Have: Expert-level Python (Pandas, modelling libraries such as Scikit-learn) SQL AWS cloud experience Proven end-to-end ownership of data science solutions Model explainability (SHAP, LIME, feature importance) Ability to build simple dashboards or web apps (Streamlit More ❯

models. Deep understanding of mathematical and statistical modelling, including complex probability distributions and stochastic methods. Highly proficient in Python for modelling, data manipulation, and analysis (NumPy, pandas, SciPy, scikit-learn, etc.). Preferred Qualifications Advanced degree (MSc or PhD) in a quantitative discipline such as Mathematics, Statistics, Physics, Computer Science, or Engineering. Experience in sports modelling, market pricing More ❯

models. Deep understanding of mathematical and statistical modelling, including complex probability distributions and stochastic methods. Highly proficient in Python for modelling, data manipulation, and analysis (NumPy, pandas, SciPy, scikit-learn, etc.). Preferred Qualifications Advanced degree (MSc or PhD) in a quantitative discipline such as Mathematics, Statistics, Physics, Computer Science, or Engineering. Experience in sports modelling, market pricing More ❯

drives user clicks - A functional internal tool for non-technical stakeholders - Documentation and guidance for productionisation Required Skills Must-Have: Expert-level Python (Pandas, modelling libraries such as Scikit-learn) SQL AWS cloud experience Proven end-to-end ownership of data science solutions Model explainability (SHAP, LIME, feature importance) Ability to build simple dashboards or web apps (Streamlit More ❯

modern ML frameworks, cloud technologies, and emerging AI domains such as computer vision or GenAI. Responsibilities: Develop, train, and evaluate machine learning models using Python and popular frameworks (scikit-learn, TensorFlow, PyTorch) Conduct exploratory data analysis, feature engineering, model optimization, and apply statistical modeling techniques Build and deploy ML models on AWS SageMaker, collaborating with MLOps engineers to … data science or applied machine learning in an enterprise setting Strong understanding of AWS services, particularly SageMaker, S3, and Bedrock Proficiency in Python with experience using NumPy, pandas, scikit-learn, and one deep learning framework (PyTorch or TensorFlow) Experience working with structured and unstructured data, using SQL or Pandas for data manipulation Experience using Git, Jupyter Notebooks, and More ❯

ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent projects) Strong Python skills with PyTorch, Hugging Face or scikit-learn Experience experimenting with LLMs (fine-tuning, embeddings, prompt chaining etc.) A passion for turning messy real-world data into something powerful and production-ready Excitement about being the More ❯

ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent projects) Strong Python skills with PyTorch, Hugging Face or scikit-learn Experience experimenting with LLMs (fine-tuning, embeddings, prompt chaining etc.) A passion for turning messy real-world data into something powerful and production-ready Excitement about being the More ❯

ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent projects) Strong Python skills with PyTorch, Hugging Face or scikit-learn Experience experimenting with LLMs (fine-tuning, embeddings, prompt chaining etc.) A passion for turning messy real-world data into something powerful and production-ready Excitement about being the More ❯

ideas to life What they’re looking for: 1–3 years’ experience in applied ML/AI (or equivalent projects) Strong Python skills with PyTorch, Hugging Face or scikit-learn Experience experimenting with LLMs (fine-tuning, embeddings, prompt chaining etc.) A passion for turning messy real-world data into something powerful and production-ready Excitement about being the More ❯

For Strong hands-on experience with machine learning engineering at scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets financial or otherwise and turn them into production-ready More ❯

For Strong hands-on experience with machine learning engineering at scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production-ready More ❯

For Strong hands-on experience with machine learning engineering at scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production-ready More ❯

For Strong hands-on experience with machine learning engineering at scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production-ready More ❯

For Strong hands-on experience with machine learning engineering at scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production-ready More ❯