76 to 100 of 529 scikit-learn Jobs

development. Machine Learning (ML): • Deep understanding of machine learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and More ❯

development. Machine Learning (ML): • Deep understanding of machine learning principles, algorithms, and techniques. • Experience with popular ML frameworks and libraries like TensorFlow, PyTorch, scikit-learn, or Apache Spark. • Proficiency in data preprocessing, feature engineering, and model evaluation. • Knowledge of ML model deployment and serving strategies, including containerization and More ❯

people Accountability: Owns and takes responsibility for the quality and delivery of the assigned tasks Desired skills Machine Learning and Deep Learning Frameworks: Scikit-learn, TensorFlow, PyTorch, Keras etc. Communication: Effectively communicates complex technical concepts to a diverse audience including technical, and non-technical stakeholders, both verbally and More ❯

workflows, and analytical processes. Your skills and experience 5+ years of experience in data science. Experience with data science libraries (e.g., NumPy, pandas, scikit-learn). Proficiency in working with large datasets, data wrangling, and data preprocessing. Experience in data science, statistical modelling, and data analytics techniques. Experience More ❯

all domains: data pre-processing and post-processing, machine learning, deep learning, time-series algorithms, explainability methods and more, using Python packages (including Scikit-Learn, Pandas, NumPy, NLTK, etc.). Preferred skills and technical familiarity At least 4 years of proven experience in Data Science. Sc./M.Sc. More ❯

least one programming language commonly used in data science (e.g., Python, R). Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy, scikit-learn in Python; dplyr, ggplot2 in R). Experience with SQL and working with relational databases. Excellent problem-solving and analytical skills with the More ❯

such as STEM subject or Economics). Proficiency in Python, with a solid understanding of Python libraries (such as NumPy, pandas, Polars, and scikit-learn) for data manipulation and statistical modeling. A minimum of 5 years experience working with Futures order book market data, with strong familiarity in More ❯

development. Deep understanding of data modelling, data access, and data storage techniques. Familiarity with machine learning frameworks and data visualization tools (e.g., TensorFlow, Scikit-learn, Tableau, Power BI). Exceptional problem-solving skills and the ability to lead a team under tight deadlines. Excellent communication skills for effective More ❯

. Expertise in maintaining and deploying a notebook-based data science environment (JupyterHub). Experience in advanced Python data science packages (Pandas, NetworkX, Scikit-Learn, PyTorch or TensorFlow/Keras, Matplotlib or Plotly, etc.) _ Compensation ranges encompass a total compensation package and are a general guideline only and More ❯

into practical applications, particularly in decision-support, simulations, strategic planning, or operational analysis. Proficiency in AI and machine learning frameworks (e.g., TensorFlow, PyTorch,scikit-learn) and AI integration techniques (e.g., API deployment, model fine-tuning, reinforcement learning). Experience using generative AI models, in particular Large Language Models More ❯

Prefect Experience applying supervised and unsupervised machine learning techniques to real-world problems Proficient with machine learning libraries such as TensorFlow, PyTorch, and Scikit-Learn Familiarity with neural network architectures for sequence modeling (LSTM-RNN, Transformers), classification (CNN), and data generation (GANs) Experience with cloud platforms and services More ❯

databases, software engineering, cloud computing especially AWS) and data science (machine learning processes). Proficiency in Python and frameworks such as PyTorch, TensorFlow, scikit-learn, with some knowledge of LangChain, RAGAS, and CI/CD. Growth mindset and eagerness to learn new challenges. Willingness to travel and More ❯

databases, software engineering, cloud computing especially AWS) and data science (machine learning processes). Proficiency in Python and frameworks such as PyTorch, TensorFlow, scikit-learn, with some knowledge of LangChain, RAGAS, and CI/CD. Growth mindset and eagerness to learn new challenges. Willingness to travel and More ❯

or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI More ❯

or coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI More ❯

consulting, with strong ETL pipeline development and cloud-based environment experience (Azure, AWS, DataBricks, or Snowflake). Proficient in Python (including numpy, pandas, scikit-learn), SQL, dimensional modeling, Power BI, Git, CI/CD, and VSCode/PyCharm. Proficiency in English and French is a strong advantage Detail More ❯

and solid understanding of machine learning and deep learning methods. Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas). Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with More ❯

such as HuggingFace, Langchain, and OpenAI. Extensive hands-on industry data science experience, leveraging typical machine learning and data science tools including pandas, scikit-learn, and TensorFlow/PyTorch. Experience building production-grade machine learning deployments on AWS, Azure, or GCP. Experience communicating and/or teaching technical More ❯

science or machine learning with a focus on unstructured data processing and AI-based extraction solutions. Proficiency in Python and ML libraries (e.g., scikit-learn, PyTorch, spaCy, Hugging Face Transformers). Hands-on experience with LLMs (e.g., GPT, BERT, Claude) and prompt engineering or fine-tuning approaches. Strong More ❯

Blue Prism. Strong knowledge of Python, R, or JavaScript for scripting and machine learning model development. Experience with machine learning frameworks such as scikit-learn, TensorFlow, PyTorch, or similar. Proficiency in working with relational databases (SQL Server, Oracle, PostgreSQL) and APIs. Solid understanding of software development lifecycle (SDLC More ❯

working with real-world data sets and building scalable models from big data - Experience with modern modeling tools and frameworks such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow - Experience with large scale distributed systems Our inclusive culture empowers Amazonians to deliver the best results for our customers. More ❯

working with real-world data sets and building scalable models from big data - Experience with modern modeling tools and frameworks such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow - Experience with large scale distributed systems Our inclusive culture empowers Amazonians to deliver the best results for our customers. More ❯

such as AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and More ❯

IOI, Top Coder, Kaggle and other competitions are preferred. Strong analytical and statistical modeling skills. Experience with machine learning (Generative AI) frameworks (e.g., scikit-learn, TensorFlow, PyTorch, Langchain, Weaviate, Langgraph, LlamaIndex). Proven track record of applying data science to solve real-world problems. Excellent communication and collaboration More ❯

learning models and algorithms in real-world applications. - Strong proficiency in Python programming and popular machine learning libraries/frameworks (eg, TensorFlow, PyTorch, scikit-learn). - Deep understanding of machine learning concepts and techniques, including supervised/unsupervised learning, deep learning, reinforcement learning, etc. - Strong communication and interpersonal More ❯