1 to 25 of 111 Permanent scikit-learn Jobs in the South East

Selenium). Strong knowledge of data cleaning, standardization, and normalization techniques Experience with data analysis and modeling using libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow. Familiarity with SQL and database management systems (e.g., PostgreSQL, MySQL). Experience with cloud platforms (e.g., AWS, Azure, GCP) and big More ❯

Selenium). Strong knowledge of data cleaning, standardization, and normalization techniques Experience with data analysis and modeling using libraries such as Pandas, NumPy, Scikit-learn, or TensorFlow. Familiarity with SQL and database management systems (e.g., PostgreSQL, MySQL). Experience with cloud platforms (e.g., AWS, Azure, GCP) and big More ❯

experience in building production-grade machine learning systems Strong programming skills in Python, with expertise in ML frameworks such as TensorFlow, PyTorch, and scikit-learn Proven track record of developing predictive models for financial applications Deep understanding of machine learning algorithms, statistical modeling, and data processing techniques Experience More ❯

experience in building production-grade machine learning systems Strong programming skills in Python, with expertise in ML frameworks such as TensorFlow, PyTorch, and scikit-learn Proven track record of developing predictive models for financial applications Deep understanding of machine learning algorithms, statistical modeling, and data processing techniques Experience More ❯

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 More ❯

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 More ❯

Proven track record delivering ML/AI solutions in complex, real-world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to More ❯

Proven track record delivering ML/AI solutions in complex, real-world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to More ❯

and Visualisation tools (Cassandra, Hadoop, Spark, Tableau) Desirable: Experience within an AI/ML-focused team or projects Familiarity with ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow) Exposure to model validation, explainability, or regulatory AI contexts Why Join? Work with a top-tier AI/ML team on More ❯

or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI More ❯

or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI More ❯

Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with More ❯

Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with More ❯

with GPUs to develop models, handling terabyte size datasets Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, mlr, mllib, Scikit-learn, caret etc - excellence in at least one of these is highly desirable. You should be able to work hands-on in Python, R More ❯

with GPUs to develop models, handling terabyte size datasets Experience with common data science toolkits, such as R, Weka, NumPy, MatLab, mlr, mllib, Scikit-learn, caret etc - excellence in at least one of these is highly desirable. You should be able to work hands-on in Python, R More ❯

similar projects Strong track record of delivering machine learning or AI projects end-to-end Hands-on skills in Python, with frameworks like Scikit-learn, TensorFlow, PyTorch, or PySpark Deep understanding of data science best practices, including MLOps Strong stakeholder communication skills-able to translate complex insights into More ❯

similar projects Strong track record of delivering machine learning or AI projects end-to-end Hands-on skills in Python, with frameworks like Scikit-learn, TensorFlow, PyTorch, or PySpark Deep understanding of data science best practices, including MLOps Strong stakeholder communication skillsable to translate complex insights into business More ❯

in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or More ❯

in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or More ❯

science methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best More ❯

science methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best More ❯

science methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best More ❯

science methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best More ❯

in machine learning engineering, with a strong focus on productionizing ML models and MLOps. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines More ❯

in machine learning engineering, with a strong focus on productionizing ML models and MLOps. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines More ❯