1 to 25 of 216 scikit-learn Jobs

data quality, governance, and compliance throughout the analytics lifecycle. Required Skills & Qualifications: Strong proficiency in Python, SQL , and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch . Hands-on experience with ML algorithms and deep learning architectures. Expertise in NLP techniques and frameworks, familiarity with LLM fine ...

language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries ...

language) and in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries ...

automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation ...

automation scripts with proper logging, testing (pytest), and documentation. AI & Machine Learning Frameworks - Deep expertise in AI/ML frameworks including TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers. Experience building, training, and deploying machine learning models for classification, regression, clustering, and NLP tasks. Understanding of model evaluation ...

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. ...

Solutions Engineer AI Solutions, B2B, B2C, Azure, AI Foundry, Open-AI, Microsoft Copilot Studio, Machine Learning, Python, TensorFlow, PyTorch, scikit-learn, Large Language Models, LLM, Data preprocessing, REST API, Microservices architecture, MLOps, CI/CD for ML, Power-BI, Docker, Kubernetes, AI Ethics, Cloud Platforms, AWS, Google Cloud ...

Python and its core data science libraries: Pandas, NumPy, and SciPy. Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch. Statistics & Math: Strong foundation in statistical modeling, probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra for understanding model ...

Python and its core data science libraries: Pandas, NumPy, and SciPy . Machine Learning: Deep, practical experience with popular ML frameworks and libraries: scikit-learn, TensorFlow, or PyTorch . Statistics & Math: Strong foundation in statistical modeling , probability, hypothesis testing, regression analysis, and multivariate calculus/linear algebra ...

Python Understanding of machine learning fundamentals (supervised/unsupervised learning, model evaluation, overfitting, etc.) Experience with common ML libraries such as PyTorch, TensorFlow, scikit-learn , or similar Solid foundation in data structures, algorithms, and software engineering principles Strong problem-solving skills and attention to detail Excellent communication skills ...

Prior experience in manufacturing, industrial, or operations-focused environments is strongly preferred. Technical Skills Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, and PyTorch. Solid SQL skills for data querying, transformation, and analysis. Experience with data visualization tools such as Power BI or Tableau. ...

like AWS, Google Cloud, or Azure. Familiarity with containerization technologies like Docker. Knowledge of microservices architecture. Understanding of machine learning libraries (e.g., TensorFlow, Scikit-learn) is a plus. Experience with continuous integration and continuous deployment (CI/CD) pipelines. We are an equal opportunity employer. All aspects ...

feature effectiveness. Ability to navigate large, complex, or ambiguous datasets and translate analysis into clear, actionable insights. Experience using common ML libraries (e.g. scikit-learn, PyTorch, TensorFlow, or similar). Exposure to cloud-based data or ML platforms (AWS, GCP, Azure or similar). Strong data visualisation ...

into reliable, scalable systems. Essential experience includes: Commercial experience developing and deploying machine learning models in Python Proficiency with ML frameworks such as scikit-learn, XGBoost, PyTorch or TensorFlow Strong experience delivering ML solutions using AWS services (e.g. SageMaker, Lambda, S3) Expertise in experiment design, including hypothesis formulation ...

time-series forecasting and spatio-temporal modeling, ideally applied to weather or energy systems. Strong proficiency in Python (Pandas, NumPy, PyTorch, TensorFlow, scikit-learn, Lightning, or equivalent). Solid understanding of data engineering and ML infrastructure Experience deploying ML models to cloud-native environments (Kubernetes, Docker, AWS/ ...

related quantitative field, or 8+ years of relevant or equivalent experience Strong proficiency in Python and modern data science/ML libraries (Pandas, Scikit learn, PyTorch/TensorFlow, Keras, LangChain, etc.) Proven expertise in building, deploying, and maintaining ML/AI models in AWS and/or Azure ...

accuracy, drift, bias) and rollback plans. Collaborate with data engineers and AI engineers on interfaces and SLAs. Required Skills & Experience Python (pandas, NumPy, scikit-learn; PyTorch/TF a plus). Feature engineering, data quality validation, model training and optimisation. MLOps: experiment tracking (e.g., MLflow), model registry ...

Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries ...

Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries ...

junior colleagues and share learnings across the team. Requirements: 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 ...

additional experience with other languages is a plus Experience working with tools and frameworks such as Spark, Kafka, Airflow, MLflow, TensorFlow, PyTorch, Scikit-learn, etc. Excellent communication and interpersonal skills; ability to work with both technical and business stakeholders. Strong command of German and English language (both verbal ...

talented ML Ops Engineer to join our growing teams. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow ...

such as NLP, computer vision, audio, graphs, time-series or tabular data Strong Python skills and experience with common libraries (e.g. pandas, NumPy, scikit-learn, PyTorch, Transformers, statsmodels, PyMC) Understanding of software engineering and ML best practices, including version control, packaging and model deployment Experience training and deploying ...

automation of analytical workflows. Collaborate with traders, quants, and technologists to identify data-driven opportunities. Profile Strong programming skills in Python (pandas, NumPy, scikit-learn) and SQL. Experience in data science , machine learning, and predictive modelling. Background in data engineering (ETL pipelines, streaming tech like Kafka). Familiarity ...

Learning Engineer, ideally within Financial Services, FinTech, or a regulated environment Strong Python skills and hands-on experience with ML libraries (TensorFlow, PyTorch, scikit-learn) Experience deploying and supporting ML models in production Solid understanding of data pipelines, versioning, testing, and software engineering best practices Experience working with ...