51 to 75 of 246 Permanent scikit-learn Jobs

on experience in AI or ML in a professional environment (3-5 years preferred) Strong knowledge of machine learning model development, deployment, and modern ML libraries (TensorFlow, PyTorch, scikit-learn, etc.) Solid programming background with experience using statistical and signal analysis libraries Experience with neural network architectures including deep learning models Understanding of transformer architectures and attention mechanisms More ❯

machine learning Proven experience working with consumer behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or More ❯

machine learning Proven experience working with consumer behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or More ❯

Strong python programming skills as evidenced by earlier work in data science or software engineering. 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 grasp of essentially all of More ❯

and deploying LLMs, with tools 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 concepts to non-technical and More ❯

and deploying LLMs, with tools 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 concepts to non-technical and More ❯

we do require the ability 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 grasp of essentially all of More ❯

we do require the ability 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 grasp of essentially all of More ❯

implementing efficient data pipelines, including performance tuning and optimization. Proven ability to apply machine learning techniques to real-world problems. Familiarity with core libraries such as Pandas, NumPy, Scikit-learn, SciPy, and Polars is expected. Experience with digital signal processing, mobile sensor physics, or behavioural signal design. Proven track record of designing and delivering scalable data products, driving More ❯

/experience: Proven track record of delivering commercial value using supervised machine learning techniques. Advanced Python programmer, and experience with data manipulation and analysis libraries (e.g., NumPy, Pandas, scikit-learn) Advanced knowledge of data science technologies including tooling and platforms. Proficient in SQL and Git. Ability to drive projects from initiation to completion. Keen interest in emerging Machine More ❯

frameworks. High-growth Experience: Prior experience working in high-growth environments, ideally start-ups or scale-ups Coding Skills: Proficient in Python, SQL, and one of Pytorch, Tensorflow, Scikit-learn, with daily experience in writing, debugging, and optimising code. ML Ops Knowledge: Familiarity with tools like MLflow, Kubeflow, or Vertex AI, and experience implementing CI/CD pipelines More ❯

NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and data storage solutions, including Snowflake. More ❯

NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine learning libraries like scikit-learn, PyTorch, TensorFlow, and SciPy. Hands-on experience working with multi-modal data (images, text) and relevant ML techniques. Experience with cloud technologies and data storage solutions, including Snowflake. More ❯

collaborative, face-to-face, and iterative development environment. Skills & Experience Strong foundation in applied mathematics, statistics, or machine learning. Experience building and deploying models in Python (pandas, NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow More ❯

collaborative, face-to-face, and iterative development environment. Skills & Experience Strong foundation in applied mathematics, statistics, or machine learning. Experience building and deploying models in Python (pandas, NumPy, scikit-learn, etc.). Comfort working with large and complex datasets, including data wrangling and exploratory analysis. Experience (or strong interest) in GPU-powered model development (e.g. using PyTorch, TensorFlow More ❯

data science or data engineering solutions into production. You're comfortable writing production-grade code, not just notebooks. Strong Python and SQL skills, including the basic libraries (Pandas, Numpy, ScikitLearn). You value writing clean, maintainable, and tested code. Proven ability to design, build, and maintain data pipelines and tools from scratch that are reliable, maintainable, and scalable. Strong communicator More ❯

biggest names in private equity. Ideal Candidate Experience: 5+ years in data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience with More ❯

biggest names in private equity. Ideal Candidate Experience: 5+ years in data science roles, preferably in fast-moving or early-stage environments Languages & Tools: Strong Python (Pandas, NumPy, Scikit-learn, TensorFlow or PyTorch) Advanced SQL AWS MLOps tooling (e.g., MLflow, SageMaker, or similar) Bonus Points For: Knowledge of LLMs, RAG pipelines, prompt engineering, or agentic interfaces Experience with More ❯

on experience in AI or ML in a professional environment (3-5 years preferred) • Strong knowledge of machine learning model development, deployment, and modern ML libraries (TensorFlow, PyTorch, scikit-learn, etc.) • Solid programming background with experience using statistical and signal analysis libraries • Experience with neural network architectures including deep learning models • Understanding of transformer architectures and attention mechanisms More ❯

to-text or customer feedback analysis Ability to contribute to client discussions, understand business needs, and translate them into ML solutions Familiarity with modern ML frameworks (e.g. HuggingFace, Scikit-learn, PyTorch) Comfortable working in a consultancy-style environment with multiple projects Nice to Have Experience with prompt engineering or fine-tuning LLMs Cloud platform experience (Azure, GCP preferred More ❯

and maintain scalable microservices using RESTful APIs and containerised services (Docker/Kubernetes). Integrate AI/ML models into applications using Python , leveraging frameworks such as TensorFlow , scikit-learn , or PyTorch . Collaborate with cross-functional teams including DevOps, Data Science, and UI/UX to implement features and optimise performance. Write clean, maintainable, and efficient code More ❯

and maintain scalable microservices using RESTful APIs and containerised services (Docker/Kubernetes). Integrate AI/ML models into applications using Python , leveraging frameworks such as TensorFlow , scikit-learn , or PyTorch . Collaborate with cross-functional teams including DevOps, Data Science, and UI/UX to implement features and optimise performance. Write clean, maintainable, and efficient code More ❯

new. You should have: 2+ years of experience in machine learning or data science roles Strong programming skills in Python and experience with ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Solid understanding of machine learning algorithms and statistical methods Experience working with cloud platforms (AWS, GCP, or Azure) Familiarity with MLOps tools and practices is a plus A More ❯

experience with statistical modelling or machine learning techniques (regression analysis, clustering, classification, predictive modelling) through coursework, internships, or independent projects You are proficient in Python (especially pandas, numpy, scikit-learn, or similar libraries) and comfortable performing data analysis using Jupyter notebooks or similar tools You are comfortable writing clear, efficient SQL for extracting, cleaning, and preparing datasets, demonstrated More ❯

programming in Java/Python, including API integrations Knowledge of RESTful API development and integration Understanding of version control systems (e.g., Git) Specific tools include: Python Libraries like Scikit-learn or TensorFlow SQL and NoSQL databases Soft skills include: Self-starter Collaborative Fast-paced and adaptable to change Attention to detail Strong problem-solving skills Excellent communication skills More ❯