151 to 175 of 234 scikit-learn Jobs in the UK

data services such as S3, Glue, Lambda, Redshift and Athena Solid data modelling experience Experience supporting ML workloads using PyTorch, TensorFlow or Scikit-learn (desirable) MLflow (desirable) Exposure to Kubernetes or Terraform (beneficial but not required) We are an equal opportunities employer and welcome applications from all suitably ...

online) Solid understanding of statistical methods, including GLMs and modern ML techniques Proven ability to build and deploy production-quality Python applications (pandas, scikit-learn) Experience with DevOps and ML tooling, including Kubernetes, Docker, CI/CD, and git-based workflows Familiarity with cloud platforms (AWS) and cloud ...

equivalent experience. Solid understanding of foundational data science concepts and statistical methods. Proficiency with Python and standard data science libraries (e.g. Pandas, NumPy, Scikit-Learn). Strong problem-solving ability and enthusiasm for learning new technologies. Clear written and verbal communication skills. Curiosity to learn ...

Hands-on experience with: Data Quality Data Governance techniques Knowledge of: MLOps Feature Engineering Exposure to data analysis and ML tools such as: scikit-learn pandas NumPy XGBoost LightGBM Familiarity with orchestration tools: Apache Oozie Apache Airflow Why you’ll love it here We want to make Prima ...

history What You Bring 3+ years hands-on experience with machine learning and AI development Strong Python skills with ML frameworks (TensorFlow, PyTorch, scikit-learn) Experience with computer vision or image recognition systems Practical knowledge of recommendation systems or matching algorithms Understanding of time series forecasting and predictive ...

rules engines, and data quality checks, ability to write maintainable code. Experience using Python packages for data wrangling (e.g. Pandas, Polars), modelling (e.g. scikit-learn) and visualization (e.g. matplotlib) Experience with modern data tooling (for example, Spark, Azure Data Factory) or ability to implement equivalents with code. Proven ...

regression, clustering, ranking, NLP, or LLMs).• Data & ML Ecosystem: Familiarity with data processing libraries (e.g. Pandas, NumPy) and ML frameworks (e.g. PyTorch, Scikit-learn or XGBoost).• Growth Mindset: A genuine interest in distributed system and software design, concurrent algorithms, data structures, and software engineering.At Quantcast ...

BigQuery, Vertex AI) or equivalent cloud data platforms. Experience with geospatial tooling and libraries (e.g., QGIS, GDAL, GeoPandas). Experience with PyTorch, scikit-learn, or similar ML frameworks. Background in maritime, defense, intelligence, or energy domains. #J-18808-Ljbffr ...

causal inference Experience designing and evaluating marketing experiments and lift studies Advanced SQL skills and hands-on Python experience, ideally including pandas, scikit-learn, statsmodels, or similar libraries Familiarity with modern data platforms such as Snowflake, dbt, and cloud-based analytics environments Understanding of digital advertising platforms, attribution ...

Bring 3+ years hands-on experience developing and deploying machine learning systems. Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, scikit-learn . Experience with computer vision , image recognition , or object detection . Practical background in recommendation systems, ranking models, or matching algorithms . Strong ...

Prime Finance, securities lending, or inventory management. Familiarity with revenue and yield management strategies. Hands-on experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch). Knowledge of optimization libraries and techniques (e.g., Gurobi, CPLEX, linear/nonlinear programming). Track record of publishing research or presenting ...

looking for: Experience leading or mentoring a team of data scientists, scientists or engineers Hands-on data science in Python (NumPy, SciPy, pandas, scikit-learn or similar), turning exploratory work into quantified results Heavy, day-to-day use of AI tools in your own technical work, such ...

trading, or prediction market platforms (Polymarket, Manifold, etc.) Quantitative background in maths, statistics, or probability theory ML experience including random forests, regression models, scikit-learn, and PyTorch AWS infrastructure experience deploying containerised applications and managing cloud environments (EC2, Lambda, RDS) Open-source contributions to AI or crypto projects ...

ensemble techniques (e.g., Gradient Boosted Trees, Random Forests). Core Technical Proficiency: High proficiency in Python for data science (including libraries like Pandas, Scikit-Learn, XGBoost/LightGBM) and SQL. Large-Scale Data Expertise: Demonstrable experience working with very large, complex, and sometimes messy datasets to build effective ...

. Theoretical proficiency in numerical computing, online algorithms, data structures, networking, databases, and operating systems. Familiarity with typical quantitative research toolchains including Numpy, Polars, Scikitlearn, Pytorch, etc. DevOps: version control, testing frameworks, release processes, build systems. Excellent communication, problem-solving, and analytical skills. Preferred Experience Extremely strong computer science ...

novel alpha signals Deep understanding of financial markets and market micro-structure Exceptional analytical and problem solving skills Expertise in using pandas, numpy, scikit-learn, statsmodels-tsa, TensorFlow, Keras, and Matplotlib libraries for data analysis Comfortable taking ownership of projects and responsibilities with minimum supervision At least ...

looking for 5+ years in ML/AI engineering with models shipped to production. Strong Python and the modern ML stack (PyTorch, scikit-learn, etc.). Hands‐on experience with LLMs, embeddings, and retrieval‐augmented generation. Able to balance research curiosity with practical, shippable outcomes. Creative, experimental ...

looking for 5+ years in ML/AI engineering with models shipped to production. Strong Python and the modern ML stack (PyTorch, scikit-learn, etc.). Hands‐on experience with LLMs, embeddings, and retrieval‐augmented generation. Able to balance research curiosity with practical, shippable outcomes. Creative, experimental ...

/LangChain/LangGraph/AI Agents/Enterprise Search/Neural Networks/Model Deployment/Edge AI/TensorFlow/scikit-learn/Linux/Git/Machine Learning/Artificial Intelligence/Computer Science/Mathematics/Statistics RedTech Recruitment Ltd focus on finding roles ...

Learning, Natural Language Processing (NLP), or Artificial Intelligence . Proficiency with core AI/ML libraries and languages, including Python, PyTorch/TensorFlow, Scikit-Learn, and LLM integration frameworks . Demonstrable experience with data preprocessing, model fine-tuning, evaluation metrics, and optimizing inference performance. Key Responsibilities & Duties Design ...

from data curation, collection and preparation to model choice and hyperparameter tuning, to model deployment. You have experience with PyTorch, scikit-learn, MLFlow, etc. Practical experience building LLM-based agents, improving them through metrics-driven evaluation , ideally including research loops where agents propose, run and evaluate experiments ...

library scales and how models reach deployed units. The Stack Language: Python, end to end. Signal processing and ML: NumPy, SciPy, scikit-learn, PyTorch. Backend and interface: FastAPI, Flask or a comparable lightweight framework. Cloud: Standard AWS, GCP or Azure SDKs. Nothing exotic. You are welcome to propose ...

real business content Working knowledge of Python and SQL for data analysis, including pandas and notebook-based workflows, and one or more of: scikit-learn, spaCy (or another NLP library), or graph libraries Experience applying data-science techniques (statistical analysis, similarity, clustering, entity/relationship extraction, topic modelling ...

real business content Working knowledge of Python and SQL for data analysis, including pandas and notebook-based workflows, and one or more of: scikit-learn, spaCy (or another NLP library), or graph libraries Experience applying data-science techniques (statistical analysis, similarity, clustering, entity/relationship extraction, topic modelling ...

instinct for leakage, bias and overfitting in messy real-world data. Strong ML fundamentals across classical ML and deep learning (pandas, scikit-learn, XGBoost or LightGBM, PyTorch), and the judgement to tell when a language model is the wrong tool. A deep understanding of how modern models ...