26 to 50 of 246 Permanent scikit-learn Jobs

degree in Data Science, Mathematics, Computer Science, Statistics, or a related field. 🧠 Solid understanding of data analysis, machine learning concepts, and statistical methods. 🐍 Proficiency in Python (e.g., Pandas, Scikit-learn, NumPy) or R, with exposure to tools like Jupyter, SQL, or cloud platforms (e.g., AWS, GCP). 📊 Experience working with data—through academic projects, internships, or personal work More ❯

to real-world use cases Contribute to code reviews, testing, and documentation Required Skills & Experience Strong proficiency in Python and its AI/ML ecosystem (e.g. NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow) Experience with machine learning model development , training, and deployment Familiarity with LLMs , NLP , or computer vision techniques Solid understanding of software engineering principles and version control More ❯

learning. Optimization : Continuously improve machine learning infrastructure and production workflows. Strong technical foundation in machine learning and software engineering Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (AWS, GCP, Azure) Experience with CI/CD pipelines for machine learning (e.g., Vertex AI) Familiarity with data processing tools like Apache Beam/ More ❯

a compelling and actionable way Mentor junior data scientists and contribute to the evolution of data science standards and practices Key Skills & Technologies Technical: Strong in Python (pandas, scikit-learn, XGBoost, LightGBM, etc.) Proficient in SQL for complex customer data extraction and manipulation Experience with customer analytics techniques: segmentation, RFM analysis, clustering, time-series, A/B testing More ❯

a compelling and actionable way Mentor junior data scientists and contribute to the evolution of data science standards and practices Key Skills & Technologies Technical: Strong in Python (pandas, scikit-learn, XGBoost, LightGBM, etc.) Proficient in SQL for complex customer data extraction and manipulation Experience with customer analytics techniques: segmentation, RFM analysis, clustering, time-series, A/B testing More ❯

Hands-on experience with ML techniques such as XGBoost, deep neural networks, and transformers Practical knowledge of ML libraries and frameworks such as Fastai, Keras, TensorFlow, PyTorch, and Scikit-learn Ability to research, understand, and apply emerging machine learning techniques Programming & Data Engineering Proficiency in programming languages such as Python (preferred) and C++ Experience working with structured and More ❯

in a quantitative field. Proven experience of large-scale data analysis and hypothesis testing. Strong proficiency in statistical analysis and predictive modeling. Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. Excellent problem-solving skills and attention to detail. Strong communication skills with the ability to present complex data insights to More ❯

previous management or mentorship. Have good communication skills. Nice to have Experience deploying LLMs and agent-based systems Our technology stack Python and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc. MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow Monitoring: New Relic CI/ More ❯

previous management or mentorship. Have good communication skills. Nice to have Experience deploying LLMs and agent-based systems Our technology stack Python and associated ML/DS libraries (scikit-learn, numpy, pandas, LightGBM, LangChain/LangGraph, TensorFlow, etc...) PySpark AWS cloud infrastructure: EMR, ECS, ECR, Athena, etc. MLOps: Terraform, Docker, Spacelift, Airflow, MLFlow Monitoring: New Relic CI/ More ❯

/ML, LLMs, and GenAI technologies. To Be Successful in The Role, You Will Have Required Skills: Proficiency in Python and machine learning framework s (e.g., TensorFlow, PyTorch, Scikit-Learn). Hands-on experience with OpenAI APIs and Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with data manipulation More ❯

focus on NLP and AI Advanced and hands on experience using: Python, Databricks, Azure ML, Azure Cognitive Service, Ads Data Hub, BIQuery, SAS, R, SQL, PySpark, Numpy, Pandas, Scikit Learn, TensorFlow, PyTorch, AutoTS, Prophet, NLTK Experience with Azure Cloud technologies including Azure DevOps, Azure Synapse, MLOps, GitHub Solid experience working with large datasets and developing ML/AI More ❯

production Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or Engineering - or equivalent Proficiency in Python and relevant data science libraries (NumPy, pandas, scikit-learn etc.) Experience with SQL, Power BI, Git & GitHub Strong knowledge of Machine Learning Algorithms and respective theory Ability to work within a team, collaborating effectively with colleagues Strong More ❯

roles Creative problem-solving and solution scoping Strong grasp of mathematical, statistical concepts, and machine learning algorithms Proficiency in Python and data science libraries for example NumPy, Pandas, Scikit-learn, Keras SQL proficiency Experience with cloud environments for example Google Cloud Platform Version control management Ability to work efficiently without compromising quality Effective communication and data storytelling skills More ❯

augmented generation systems. Qualifications: 3+ years of experience delivering full-stack AI/ML applications in production. Proficiency in Python, especially with ML libraries such as TensorFlow, PyTorch, scikit-learn, and backend frameworks like FastAPI, Django, Flask. Experience with frontend frameworks: React, Vue, or Angular. Hands-on experience building and scaling ML models (LLMs, NLP, classification) and deploying More ❯

a quantitative field Deep theoretical knowledge of statistical methods and ML algorithms and their practical applications. Strong proficiency in SQL and Python, especially with core ML libraries (e.g. scikit-learn, XGBoost, SciPy, PyTorch) Extensive hands-on experience in taking advanced statistical/ML solutions from prototype to production and delivering high-impact outcomes to complex business problems Proactive More ❯

priorities, meet deadlines, and deliver on project objectives. Masters degree in a STEM field (maths, science, engineering etc.) or equivalent Strong programming skills in Python (e.g., NumPy, Pandas, scikit-learn, TensorFlow/PyTorch). Demonstrable experience in creating and developing Python libraries. Demonstrable experience designing, implementing and training machine learning models from scratch. Strong foundations in applied mathematics More ❯

of LLM outputs Good foundational knowledge of standard machine learning algorithms and statistical methods Proficient in python and its standard data science and ML libraries (e.g., numpy, pandas, scikit-learn, boosting and data visualization libraries) Practical experience in data processing and feature engineering for machine learning applications Ability to write robust production-ready Python code Good communication and More ❯

Experience in statistical modeling. Experience with Power BI, Power Query, Power Automate, Power Apps, MS Excel, Python, and SQL. Experience using Python or R packages and libraries (e.g., scikit-learn, pandas, plotly, shiny, etc.) to develop predictive analyses and machine learning models. Preferred Experience: Preferred: Experience with cloud computing/storage, data lakes/warehouses. Preferred: Experience with More ❯

with an eagerness to learn and contribute within a team setting. Technical Experience: Proficient in Python for data analysis, including use of key libraries (e.g. Pandas, NumPy, Scikit-learn, Matplotlib). Good working knowledge of SQL for querying and transforming structured data. Basic understanding of common machine learning techniques and ability to implement them in Python. Exposure More ❯

from understanding multimodal user queries to planning and generating MLLM responses that combine text, image, audio and video. BASIC QUALIFICATIONS - PhD - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. - Experience with neural deep learning methods and machine learning - Experience in building machine learning models for business application - PhD in NLP More ❯

from structured and unstructured datasets of varying sizes. Track record of implementing impactful models that drive sustained business results. Proficiency in the Python data science tech stack (pandas, scikit-learn, NumPy, and visualisation libraries) Experience working in a Linux-based cloud environment (e.g. GCP, Azure, AWS). Experience using git version control. Communication, stakeholder management, and problem-solving More ❯

degree in machine learning, computer science, engineering, or a related discipline, with a BSc required and an MSc considered advantageous. Experienced in using machine learning frameworks such as Scikit-learn, Keras, and PyTorch, with additional familiarity with MLFlow and AzureML seen as a positive. Have working knowledge of CI/CD practices, ML Ops, ML pipelines, automated testing More ❯

from structured and unstructured datasets of varying sizes. Track record of implementing impactful models that drive sustained business results. Proficiency in the Python data science tech stack (pandas, scikit-learn, NumPy, and visualisation libraries) Experience working in a Linux-based cloud environment (e.g. GCP, Azure, AWS). Experience using git version control. Communication, stakeholder management, and problem-solving More ❯

you We don't expect perfection, but for this senior role we are looking for someone with: Strong Python skills, particularly within the data science ecosystem (Pandas, NumPy, scikit-learn, PyTorch/TensorFlow, visualisation libraries) 4+ years of experience delivering machine learning products end-to-end in production Hands-on experience with LLMs - fine-tuning, prompt engineering, vector More ❯

qualifications: Hold an active Security clearance (Ideally Top Secret with SCI Poly) Strong programming skills in Python, with experience in machine learning libraries such as TensorFlow, PyTorch, or scikit-learn Proficient in data manipulation, feature engineering, and model evaluation techniques Solid understanding of different machine learning algorithms and their applications Experience deploying machine learning models into production environments More ❯