251 to 275 of 445 scikit-learn Jobs

and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic research More ❯

model accuracy and interpretability. Develop and validate machine learning and statistical models for prediction, classification, clustering, or optimization. Apply supervised and unsupervised learning techniques using libraries such as Scikit-learn, TensorFlow, or PyTorch. Implement NLP, time-series forecasting, or optimization algorithms based on project requirements. Evaluate models using appropriate metrics and perform hyperparameter tuning for optimal performance. Convert … analytical methodologies. Document methodologies, model logic, and validation results for audit and reproducibility. Participate in Agile ceremonies, sprint planning, and client showcases. Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Solid background in statistics, probability, and mathematical modeling. Hands-on experience with machine learning algorithms, feature engineering, and model evaluation. Familiarity with SQL, data wrangling More ❯

teams to embed AI capabilities into wider systems. Translate emerging research into practical, deployable prototypes. What we’re looking for: Strong Python skills, with experience in PyTorch, TensorFlow, scikit-learn, and LLM frameworks Solid grounding in statistics, probability, and machine learning fundamentals. Experience with cloud (AWS/GCP/Azure), Docker, and API development What our client offers More ❯

teams to embed AI capabilities into wider systems. Translate emerging research into practical, deployable prototypes. What we’re looking for: Strong Python skills, with experience in PyTorch, TensorFlow, scikit-learn, and LLM frameworks Solid grounding in statistics, probability, and machine learning fundamentals. Experience with cloud (AWS/GCP/Azure), Docker, and API development What our client offers More ❯

teams to embed AI capabilities into wider systems. Translate emerging research into practical, deployable prototypes. What we’re looking for: Strong Python skills, with experience in PyTorch, TensorFlow, scikit-learn, and LLM frameworks Solid grounding in statistics, probability, and machine learning fundamentals. Experience with cloud (AWS/GCP/Azure), Docker, and API development What our client offers More ❯

teams to embed AI capabilities into wider systems. Translate emerging research into practical, deployable prototypes. What we’re looking for: Strong Python skills, with experience in PyTorch, TensorFlow, scikit-learn, and LLM frameworks Solid grounding in statistics, probability, and machine learning fundamentals. Experience with cloud (AWS/GCP/Azure), Docker, and API development What our client offers More ❯

teams to embed AI capabilities into wider systems. Translate emerging research into practical, deployable prototypes. What we’re looking for: Strong Python skills, with experience in PyTorch, TensorFlow, scikit-learn, and LLM frameworks Solid grounding in statistics, probability, and machine learning fundamentals. Experience with cloud (AWS/GCP/Azure), Docker, and API development What our client offers More ❯

working closely with investors and engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with BI tools More ❯

working closely with investors and engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with BI tools More ❯

paced and data-rich environment. Youll need: 25+ years experience in data science or ML (not a graduate role; sports background a plus) Strong Python skills (pandas, numpy, scikit-learn, etc.) Hands-on experience with tree-based algorithms (XGBoost, LightGBM) and other ML methods Solid grasp of statistics, probability, and applied maths Proficiency in SQL , familiarity with NoSQL More ❯

working closely with investors and engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with BI tools More ❯

working closely with investors and engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with BI tools More ❯

working closely with investors and engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with BI tools More ❯

paced and data-rich environment. Youll need: 25+ years experience in data science or ML (not a graduate role; sports background a plus) Strong Python skills (pandas, numpy, scikit-learn, etc.) Hands-on experience with tree-based algorithms (XGBoost, LightGBM) and other ML methods Solid grasp of statistics, probability, and applied maths Proficiency in SQL , familiarity with NoSQL More ❯

data-rich environment. You’ll need: 2–5+ years’ experience in data science or ML (not a graduate role; sports background a plus) Strong Python skills (pandas, numpy, scikit-learn, etc.) Hands-on experience with tree-based algorithms (XGBoost, LightGBM) and other ML methods Solid grasp of statistics, probability, and applied maths Proficiency in SQL , familiarity with NoSQL More ❯

data-rich environment. You’ll need: 2–5+ years’ experience in data science or ML (not a graduate role; sports background a plus) Strong Python skills (pandas, numpy, scikit-learn, etc.) Hands-on experience with tree-based algorithms (XGBoost, LightGBM) and other ML methods Solid grasp of statistics, probability, and applied maths Proficiency in SQL , familiarity with NoSQL More ❯

rich environment. You'll need: 2-5+ years' experience in data science or ML (not a graduate role; sports background a plus) Strong Python skills (pandas, numpy, scikit-learn, etc.) Hands-on experience with tree-based algorithms (XGBoost, LightGBM) and other ML methods Solid grasp of statistics, probability, and applied maths Proficiency in SQL , familiarity with NoSQL More ❯

experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWS's machine learning infrastructure. Again this is a More ❯

experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWS’s machine learning infrastructure. Again this is a More ❯

experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWS’s machine learning infrastructure. Again this is a More ❯

experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWS’s machine learning infrastructure. Again this is a More ❯

What We're Looking For A Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or a related field. Strong experience with Python and data science libraries (Pandas, Scikit-learn, etc.). Solid understanding of machine learning concepts and algorithms . Interest in working with real-world industrial or sensor data . Exposure to Apache Airflow and/ More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large Big Data environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯

to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL and large “Big Data” environments. Command knowledge in Python and API Development Excellent grasp of software Engineering More ❯