1 to 25 of 191 Remote scikit-learn Jobs

Technical Skills: Programming & Data Tools Proficiency in Python and R for machine learning and data analysis. Experience with libraries like Pandas, NumPy, and scikit-learn for data manipulation and model building. Familiarity with data visualization tools such as Matplotlib or Plotly. Machine Learning & Model Development Experience developing and More ❯

Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code. Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or Pandas for high-performance data More ❯

Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code. Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or Pandas for high-performance data More ❯

s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field. Experience with Python, SQL, and machine learning frameworks (e.g., TensorFlow, Scikit-learn, PyTorch). Familiarity with software development, cloud computing (AWS, Azure), and algorithms. Strong analytical and problem-solving skills with the ability to work More ❯

JupyterLab or AWS Sagemaker for interactive data analysis and model development. Strong proficiency in Python and experience with libraries such as TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy and Statsmodels. Expertise in time series forecasting techniques, such as RNNs, LSTMs and GRUs. Knowledge of Grafana (or similar tools) and More ❯

techniques, with hands-on experience in either academia or industry. Proficiency in Python and experience with ML/NLP libraries like TensorFlow, PyTorch, scikit-learn, or Hugging Face. Experience working with cloud platforms such as AWS, GCP, or Azure. Familiarity with advanced NLP methods, including Prompt Engineering, Parameter More ❯

software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience More ❯

software engineering skills, including version control (Git), code reviews, and unit testing. Familiarity with common data science libraries and tools (e.g., NumPy, Pandas, Scikit-learn, Jupyter). Experience in setting up and managing continuous integration and continuous deployment pipelines. Proficiency with containerization technologies (e.g., Docker, Kubernetes). Experience More ❯

production-ready code, architect packages, and make sound architectural and procedural choices for effective shared codebases • Python and scientific computing packages (pytorch, numpy, scikit-learn, tensorflow) • Database technologies such as ElasticSearch, Neo4j, and SQL • Excellent interpersonal, verbal, and written communication skills • A flexible attitude with respect to work More ❯

like Flask, FastAPI, Pandas, PySpark, PyTorch, to name a few. Proficiency in statistics and/or machine learning libraries like NumPy, matplotlib, seaborn, scikit-learn, etc. Experience in building ETL/ELT processes and data pipelines with platforms like Airflow, Dagster, or Luigi. What's important for us More ❯

and deploying AI solutions in a business environment. Proficiency in Python and familiarity with AI frameworks and libraries such as Pandas, NumPy, PyTorch, Scikit-Learn, Streamlit, and SciPy. Strong understanding of software development principles, AI engineering, and MLOps. Experience working with cloud-based AI solutions on platforms like More ❯

and deploying AI solutions in a business environment. Proficiency in Python and familiarity with AI frameworks and libraries such as Pandas, NumPy, PyTorch, Scikit-Learn, Streamlit, and SciPy. Strong understanding of software development principles, AI engineering, and MLOps. Experience working with cloud-based AI solutions on platforms like More ❯

domains (e.g. Natural Language Processing, Computer Vision) and expert knowledge in statistics. You are proficient in the Python Machine Learning stack (NumPy, pandas, scikit-learn, TensorFlow/PyTorch), have extensive experience in software development and are skilled with various database systems (relational/NoSQL). You are experienced More ❯

and SQL, and data analysis libraries (e.g., Pandas, NumPy, SciPy, Tidyverse). Strong knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, NLTK). Experience with NLP techniques, such as named entity recognition (NER), topic modeling, semantic similarity, and knowledge graph construction. Demonstrated ability to More ❯

clients in data handling, analysis, and modeling. Working within diverse, inclusive teams. Connect to your skills and experience Proficiency in Python (pandas, numpy, scikit-learn) and R. Understanding of ML principles, algorithms, and deployment. Experience with end-to-end data science projects. Strong communication and presentation skills. Knowledge More ❯

Strong programming skills in Python or R, with proficiency in data manipulation libraries (e.g., Pandas, NumPy). Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib). Solid understanding of statistics, probability, and data-driven decision-making. Experience working with databases More ❯

Strong programming skills in Python or R, with proficiency in data manipulation libraries (e.g., Pandas, NumPy). Experience with machine learning frameworks (e.g., Scikit-Learn, TensorFlow) and data visualization tools (e.g., Tableau, Matplotlib). Solid understanding of statistics, probability, and data-driven decision-making. Experience working with databases More ❯

to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid More ❯

to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid More ❯

years experience in Data Science(perfect for second-jobbers) First-class STEM degree from a prestigious university Strong Python skills (Pandas, NumPy, Scikit-Learn) Cloud computing experience (primarily Azure but they work with all major cloud providers depending on their clients needs). SQL knowledge and database experience More ❯

years experience in Data Science(perfect for second-jobbers) First-class STEM degree from a prestigious university Strong Python skills (Pandas, NumPy, Scikit-Learn) Cloud computing experience (primarily Azure but they work with all major cloud providers depending on their clients needs). SQL knowledge and database experience More ❯

NLP Experience with transformer models (BERT, GPT, LLaMA, etc.) Proficiency in SQL, Python and ML libraries such as TensorFlow, PyTorch, Hugging Face, and Scikit-Learn Expertise in personalisation techniques (recommendation systems, user segmentation, dynamic pricing) Experience working with sensitive and business critical data, able to perform behavioural and More ❯

Data Science, Computer Science, Statistics, or related field 3+ years of experience in data science or machine learning role Proficiency in Python (pandas, scikit-learn, TensorFlow, etc.) and SQL Experience with cloud platforms (Azure preferred) and ML tools Strong understanding of machine learning concepts and model evaluation techniques More ❯

strategies across the Civil Service. Key Skills and Experience • Strong programming skills in Python, R, or SQL. • Experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch). • Proficiency in data manipulation and analysis (e.g., Pandas, NumPy, Spark). • Knowledge of data visualization tools (e.g., Power BI, Tableau More ❯

We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost. With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We tackle More ❯