1 to 25 of 254 scikit-learn Jobs

Node.js, Streamlit IDE experience: PyCharm, VS Code, JupyterLab, Eclipse, Notepad++, Sagemaker Studio, Azure ML Studio, Vertex AI Workbench Python Libraries NumPy, Pandas, Matplotlib, Scikit-learn, TensorFlow, Keras, PyTorch, PySpark, SpaCy, SciPy, NLTK, Statsmodels, Boto3, AzureSDK NLP & LLMs BERT, Word2Vec, Universal Sentence Encoder, NLTK, embeddings, fuzzy matching, topic modelling ...

production-grade analytical solutions. Hands-on experience with cloud platforms (Azure, AWS and/or Snowflake). Expertise in modern machine learning frameworks (scikit-learn, XGBoost, PyTorch, TensorFlow). Demonstrable experience delivering end-to-end ML and GenAI solutions (including RAG, LLMs, embeddings and vector databases). Strong ...

Skills (What we're looking for) Technical Skills: · Strong programming skills in Python with expertise in ML/Al libraries (e.g., TensorFlow, PyTorch, scikit-learn, Keras). · Experience working with large datasets and using tools such as Pandas, NumPy, and Matplotlib. · Proficiency with cloud platforms like AWS, Azure ...

contribute to our internal library of proprietary tools and frameworks. Technical Profile Expert Programming: Mastery of Python and its ecosystem (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Experience writing production-ready, modular, and well-tested code. Advanced Modeling: Deep theoretical and practical knowledge of Machine Learning. ...

learning techniques to unstructured data, particularly with image and geometric datasets. Proficiency with data science or machine learning libraries in Python (Pandas, NumPy, Scikit-learn, PyTorch, or TensorFlow). Solid understanding of software engineering principles, including object-oriented programming, data structures, algorithms, and design patterns. Ability to quickly ...

Computer Science, Data Science, Statistics, Mathematics, or a related field . Strong proficiency in Python and key data science libraries ( NumPy, pandas, scikit-learn, Matplotlib, Seaborn ). Basic understanding of supervised and unsupervised learning algorithms (e.g., regression, classification, clustering). Knowledge of data querying and manipulation using ...

exposure to ML lifecycle. Hands-on experience building or maintaining ML workflows or pipelines. Strong Python skills and experience with tools like MLflow, Scikit-learn, or PyTorch. Familiarity with cloud platforms (especially Azure, AWS). Good understanding of containerisation (Docker) and orchestration (e.g. Kubernetes). Exposure ...

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 ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

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/ ...

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 ...

degree in Data Science, Computer Science, Statistics, Mathematics, or a related discipline. Strong proficiency in Python or R, including libraries such as pandas, scikit-learn, NumPy, TensorFlow, or PyTorch. Solid understanding of statistical analysis, hypothesis testing, and experimental design. Hands-on experience applying a range of supervised ...

Machine Learning deployments on AWS, Azure or GCP Extensive hands-on data science experience, leveraging machine learning and data science tools (i.e., pandas, scikit-learn, PyTorch, etc.) Experience with DevOps tools: Kubernetes, Docker, Terraform, CI/CD Pipelines, GitHub/GitLab, GitOps, GitHub Actions, Jira, Jenkins, CircleCI, Datadog ...

hierarchical, mixed models/multi-level modeling Experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) Experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret) Financial Services background Genesis10 - Contract & Perm/Direct Hire Ranked a Top Staffing Firm in the U.S. by Staffing Industry Analysts ...

enterprise environments Deep understanding of algorithm selection, model complexity trade-offs, and overfitting/underfitting dynamics Strong proficiency in Python and ML ecosystems (scikit-learn, pandas, NumPy) Experience with deep learning frameworks (PyTorch or TensorFlow) Practical knowledge of deep learning architectures (CNNs, RNNs, Transformers) and when to apply ...

experience delivering end-to-end ML or AI solutions into production environments* Hands-on experience with ML frameworks such as PyTorch, TensorFlow, or scikit-learn* Experience working with LLMs, including prompt design, RAG, or fine-tuning* Experience building APIs and integrating AI systems into real products* Solid understanding ...

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 ...

conversational AI, recommendation systems, optimisation, or marketing analytics. Deep understanding of ML fundamentals across the full lifecycle. Hands‐on experience with ML frameworks (scikit‐learn, XGBoost, PyTorch, TensorFlow, LightGBM). Strong exposure to LLMs, prompt engineering, RAG, and evaluation frameworks. Familiarity with MLOps tooling: CI/CD, experiment ...

professional experience in data science and analysis 5+ years' Python, "R" or other scripting languages 2+ years' database experience ML practice - using scikit learn, tensorflow, or pytorch and perform DEA (Data exploration Analysis), clean data, model selection, feature selection/tuning, and deployment 2+ years' experience with data ...

uphold best practices for deploying ML at scale Key skills & experience: • Strong Python and software engineering fundamentals • Experience operationalising ML models (e.g. Scikit-learn, TensorFlow, PyTorch) • Hands-on cloud experience (AWS, Azure or GCP), including security considerations • Containerisation and orchestration (Docker, Kubernetes) • Solid grounding in core ML concepts ...

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 ...

enterprise environments Deep understanding of algorithm selection, model complexity trade-offs, and overfitting/underfitting dynamics Strong proficiency in Python and ML ecosystems (scikit-learn, pandas, NumPy) Experience with deep learning frameworks (PyTorch or TensorFlow) Practical knowledge of deep learning architectures (CNNs, RNNs, Transformers) and when to apply ...

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 ...

years of hands-on experience in data science, machine learning, or applied statistics. Strong Python skills with experience in ML frameworks such as scikit-learn, PyTorch, TensorFlow, or similar. Solid grounding in statistics — hypothesis testing, regression, correlation analysis, and experimental design. Experience with SQL and data manipulation ...