1 to 25 of 107 scikit-learn Jobs

Skills/Knowledge/Experience Data Science & ML Supervised and unsupervised learning Time series, NLP, recommendation systems (as applicable) Programming Python (NumPy, Pandas, Scikit learn) Optional: R, SQL Data Platforms Relational & NoSQL databases Big data frameworks (Spark, Hive, Databricks) MLOps & Deployment Model lifecycle management CI/CD pipelines ...

flows) Understanding of regulatory and compliance implications in payments Experience working in payments transformation programs Technical Strong Python skills Experience with ML libraries (Scikit-learn, TensorFlow, PyTorch, XGBoost, etc.) Experience with LLMs/GenAI frameworks (LangChain, RAG, prompt engineering, etc.) Experience in cloud (AWS/Azure/ ...

stack products Strong backend (Node.js, Python/Flask, FastAPI) and frontend (React, Next.js, Vue) fundamentals ML/data science proficiency: Python, SQL, pandas, scikit-learn, PyTorch/TensorFlow Experience with cloud platforms (AWS, GCP, Azure) and containerisation (Docker, Kubernetes) Proven ability to build data-secure, privacy-compliant infrastructure ...

learning technologies and best practices Skills and Experience • Strong programming skills in Python • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn • Experience working with SQL and large datasets • Familiarity with data pipelines, feature engineering, and model optimisation • Understanding of MLOps practices, model deployment ...

engaging with non-technical stakeholders to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI ...

GenAI: Experience with LLM APIs and Context Engineering (constructing prompts, managing context windows, evaluating behaviour). Engineering & Stack: Python: Expert level (Pandas, NumPy, Scikit-Learn). Data Engineering: Strong SQL skills and experience building data pipelines. Experience: Education: Degree in a quantitative field (Statistics, Mathematics, Computer Science, etc. ...

years of experience in Artificial Intelligence/Machine Learning . Strong programming experience in Python . Experience with TensorFlow, PyTorch, or Scikit-learn . Knowledge of data processing tools such as Pandas, NumPy . Experience with NLP, Computer Vision, or Predictive Analytics . Understanding of cloud platforms like ...

will have experience in many of the following: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments Strong experiment design skills: hypothesis formulation, A/ ...

Skilled at working with non-technical stakeholders to scope, design and deliver effective ML solutions. Proficient with the Python data science stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI ...

lifecycle, from feature engineering to deployment and monitoring Build and maintain data pipelines and production workflows using Python, TensorFlow, PyTorch, scikit-learn, AWS (S3, Lambda, SageMaker, Step Functions, Bedrock), Snowflake, and Dataiku Apply MLOps best practices, including CI/CD, automated testing, model versioning, and observability Define deployment ...

prioritisation What We're Looking For Strong operational research and optimisation background - this is a must Fluent Python, with hands-on experience of scikit-learn, pandas, numpy, Gurobi or similar OR packages Production ML/optimisation software experience - you've shipped models that run at scale Cloud platform ...

university is a great indicator, though it's your depth of applied expertise that matters most. Technically, you bring: Python fluency (NumPy, Pandas, Scikit-Learn, PyTorch) and solid TypeScript/API skills Hands-on experience with LLMs prompt engineering, evaluation, RAG architectures, safety considerations Cloud-native development ...

experience as a Machine Learning Engineer or equivalent role Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow Strong experience with cloud-based ML deployment (e.g., AWS SageMaker, Lambda, S3) Knowledge of MLOps/LLMOps tooling (e.g. ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

Python (or similar experience with a desire to develop Python skills) Familiarity with essential data science tools and libraries (e.g. NumPy, Pandas, Scikit-Learn) and machine learning (e.g. PyTorch, Tensorflow, Huggingface, LangChain, LiteLLM). A high level of competence in applied maths, statistics and scientific methods. Clear written ...

delivering ML/AI solutions into production environments Strong Python expertise and experience with modern AI/ML frameworks such as: PyTorch TensorFlow scikit-learn NumPy Pandas Hands-on experience with Generative AI, agentic AI systems, and AI testing frameworks Strong communication skills and a passion for clear ...

mixed integer programming, heuristics) Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit-learn, pandas, numpy, gurobi etc.) to solve real-life problems and visualise the outcomes (e.g. seaborn) Proficient in working with cloud platforms (AWS preferred ...

Statistics, Computer Science, Mathematics, or similar Experience delivering predictive analytics or machine learning solutions Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda, Redshift) Ability to clearly communicate insights to non-technical stakeholders Strong ...

Science, Artificial Intelligence, Mathematics, Data Science or similar Strong programming skills in Python Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn Experience working with large datasets and building data pipelines Knowledge of cloud platforms such as AWS, GCP, or Azure Experience developing and deploying ...

client in conjunction with this vacancy only. KEY SKILLS AI, Python, Machine Learning, Software Engineering, Data, APIs, Cloud, Agile, Python, TensorFlow, PyTorch, Scikit-learn, XGBoost, NLTK, OpenAI, LangChain, Pandas, NumPy, MLflow, Kubeflow, Docker, Kubernetes, Azure Machine Learning, Google Vertex ...

applications from women who are passionate about machine learning and eager to grow: Strong Python skills and experience with ML libraries (pandas, NumPy, scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, Keras, PyTorch). Familiarity with model deployment and serving tools (ONNX, TensorRT, TensorFlow Serving, TorchServe). Experience with ...