26 to 50 of 432 scikit-learn Jobs in London

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 ❯

of reinforcement learning, predictive modelling (classification and regression) and have a solid understanding of recommendation systems Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) Have experience with Spark Have experience in productionising machine learning models and/or real-time systems Have knowledge of DevOps technologies such as Docker and Terraform … or algorithms Have experience with NLP, designing, fine-tunning and developing GenAI models and building agent AI systems Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, TensorFlow, etc...) PySpark AWS cloud infrastructure: EMR, ECS, S3, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow, Jenkins More Information Enjoy fantastic perks like private healthcare More ❯

of reinforcement learning, predictive modelling (classification and regression) and have a solid understanding of recommendation systems Are proficient with Python, including open-source data libraries (e.g Pandas, Numpy, Scikit learn etc.) Have experience with Spark Have experience in productionising machine learning models and/or real-time systems Have knowledge of DevOps technologies such as Docker and Terraform … or algorithms Have experience with NLP, designing, fine-tunning and developing GenAI models and building agent AI systems Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, TensorFlow, etc...) PySpark AWS cloud infrastructure: EMR, ECS, S3, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow, Jenkins More Information Enjoy fantastic perks like private healthcare More ❯

QISQL for data access and processing (PostgreSQL preferred, but general SQL knowledge is important) Latest Data Science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., TensorFlow, MXNet, scikit-learn) Software engineering practices (coding standards, unit testing, version control, code review) Hadoop distributions (Cloudera, Hortonworks), NoSQL databases (Neo4j, Elastic), streaming technologies (Spark Streaming) Data manipulation and wrangling techniques 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 Bachelor's degree in Computer Science, Machine Learning, AI, or a related field Proven experience as a Machine Learning 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 ❯

technical skills Proficient in SQL and Python. An ability to analyse complex datasets and extract actionable insights. Experience with machine learning and deep learning frameworks (e.g. TensorFlow, PyTorch, Scikit-learn). Skilled in building credible statistical models. Knowledge of various learning algorithms (supervised, unsupervised, reinforcement). Experience with MLOps practices. Demonstrable experience building visualisations and dashboards in Tableau. More ❯

using languages such as Python, C, Julia, C++, or similar. • Strong proficiency in Python and its scientific computing/ML ecosystem (e.g., NumPy, Pandas, TensorFlow, AI Foundry, OpenAI, Scikit-learn etc.). • Solid understanding of core machine learning concepts • Hands-on experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch, Keras). • Proven understanding of More ❯

distributions, probability, bayesian stats etc.) Good working knowledge of Python Implementing end-to-end ML pipelines Hand-on experience in Python data science ecosystem (e.g. numpy, scipy, pandas, scikit-learn, matplotlib etc.) Deep Learning frameworks (TensorFlow, PyTorch, MLX) Popular classification and regression techniques Unsupervised learning & matrix factorisation algorithms Natural Language Processing (NLP) and document processing Generative AI (open 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 ❯

The financial services industry is experiencing a period of rapid transformation fueled by the power of AI. Deloitte's AI & Data Financial Services team is at the heart of this revolution, empowering our clients to leverage cutting-edge AI solutions More ❯

Are you a seasoned Data Scientist eager to collaborate with a team of top-tier innovators, tackling diverse products across various industries? If so, Nexaphaze could be the perfect fit for you. We're seeking an experienced Data Scientist to More ❯

Social network you want to login/join with: Team/Department : Data Science Team within Marketing Sciences Department Role We are looking for an ML Engineer to join our world-class Data Science team of around 8 data scientists 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 ❯

Experience with microservice architecture, API development. Machine Learning (ML): • Deep understanding of machine learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle More ❯

Experience with microservice architecture, API development. Machine Learning (ML): Deep understanding of machine learning principles, algorithms, and techniques. Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proficiency in data preprocessing, feature engineering, and model evaluation. Knowledge of ML model deployment and serving strategies, including containerization and microservices. Familiarity with ML lifecycle More ❯

track key metrics and support decision-making Collaborate with product, engineering, and business teams to translate goals into data projects Use tools like Python, R, SQL, Jupyter, Pandas, Scikit-learn, TensorFlow, Power BI, Tableau , and others Requirements Minimum Bachelor's degree in Data Science, Mathematics, Statistics, Computer Science, or a related field Proven experience as a Data Scientist More ❯

Experience with microservice architecture, API development. Machine Learning (ML): • Deep understanding of machine learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and microservices. • Familiarity with ML lifecycle More ❯

e.g., text, PDFs, audio, video) • Familiar with Machine Learning (ML) models like XGBoost, deep neural networks, transformers, Markov chains • Experienced in using Machine Learning (ML) libraries such as scikit-learn, TensorFlow, PyTorch, Keras, Hugging Face Cloud & Deployment • Hands-on experience with AWS, Azure, or GCP • Understanding of API integration and cloud-based Machine Learning (ML)/AI deployment 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 ❯

frameworks. Skills and Qualifications Skills & Expertise Strong experience in machine learning, deep learning, and statistical analysis. Expertise in Python, with proficiency in ML and NLP libraries such as Scikit-learn, TensorFlow, Faiss, LangChain, Transformers and PyTorch. Experience with big data tools such as Hadoop, Spark, and Hive. Familiarity with CI/CD and MLOps frameworks for building end 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 ❯

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 ❯