176 to 200 of 216 Permanent NumPy Jobs

clearly and enjoy working on applied problems. Key Requirements Strong experience with object detection/tracking and vision architectures. Deep knowledge of Python , PyTorch , TensorFlow , and core ML tools (NumPy, pandas, scikit-learn). Experience with evaluation metrics (Accuracy, Recall, F1, IoU). Strong problem-solving and communication skills. Bonus: Background in robotics, aviation, mobility, or edge computing. Experience deploying More ❯

clearly and enjoy working on applied problems. Key Requirements Strong experience with object detection/tracking and vision architectures. Deep knowledge of Python , PyTorch , TensorFlow , and core ML tools (NumPy, pandas, scikit-learn). Experience with evaluation metrics (Accuracy, Recall, F1, IoU). Strong problem-solving and communication skills. Bonus: Background in robotics, aviation, mobility, or edge computing. Experience deploying More ❯

scale AI applications, and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical More ❯

scale AI applications, and mentoring a team of talented data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical More ❯

Experience Current enhanced DV clearance (mandatory) Proven experience in a data science or machine learning role Strong programming skills in Python and familiarity with key data libraries (e.g. pandas, NumPy, scikit-learn) Experience with data wrangling , feature engineering, and model optimisation Understanding of data pipelines , APIs, and production deployment workflows Excellent communication skills and a collaborative approach Why Apply? Work More ❯

and concise business narratives Contributing to simple, reliable data pipelines and automated quality checks About You Minimum 1 year of commercial Data Science experience Strong hands-on Python (pandas, NumPy, scikit-learn) and SQL Sound understanding of statistics and forecasting Confident communicator - able to explain technical work clearly to non-technical audiences Why Apply Opportunity to build from scratch within More ❯

data analysis and reporting, 1+ years of experience performing data analysis in the solar industry strongly preferred Advanced skills with the Python programming language and specifically the pandas and numpy data analysis packages, 1+ years experience required, 3+ years preferred Knowledge of residential solar system equipment and operation preferred Strong analytical skills with the ability to exercise independent research Must More ❯

learning models to 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 More ❯

demonstrable proficiency across: - CORE EXPERIENCE : Strong command of Generative AI, LLMs, and RAG principles. Proven experience managing the end-to-end ML lifecycle. - TECH STACK: Proficiency in Python (Pandas, NumPy, LangChain). Deep familiarity with the [Specific Vendor]’s [Cloud Environment] AI and Data Stack (Azure ML, Azure OpenAI, Databricks). - SPECIALIZATION: Expertise in Vector databases (FAISS, Pinecone, Azure AI More ❯

ECCV) Hands-on experience training, evaluating, and deploying state-of-the-art computer vision models (e.g., YOLO, Vision Transformers, Eva) Strong Python skills and familiarity with libraries such as NumPy, pandas, scikit-learn, TensorFlow, and PyTorch Experience with ML workflows, MLOps, and best practices in model validation and evaluation Solid understanding of evaluation metrics such as Accuracy, Recall, F1, IoU More ❯

ECCV) Hands-on experience training, evaluating, and deploying state-of-the-art computer vision models (e.g., YOLO, Vision Transformers, Eva) Strong Python skills and familiarity with libraries such as NumPy, pandas, scikit-learn, TensorFlow, and PyTorch Experience with ML workflows, MLOps, and best practices in model validation and evaluation Solid understanding of evaluation metrics such as Accuracy, Recall, F1, IoU More ❯

They’re Looking For You’ve led the delivery of applied machine learning projects, ideally across commercial or regulated sectors Strong Python skills and comfort using core libraries (e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, or NLP and LLM/GenAI More ❯

They’re Looking For You’ve led the delivery of applied machine learning projects, ideally across commercial or regulated sectors Strong Python skills and comfort using core libraries (e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, or NLP and LLM/GenAI More ❯

They’re Looking For You’ve led the delivery of applied machine learning projects, ideally across commercial or regulated sectors Strong Python skills and comfort using core libraries (e.g. NumPy, Pandas), plus familiarity with deep learning tooling like PyTorch Expertise in a wide range of ML methods, including supervised and unsupervised learning, time series, or NLP and LLM/GenAI More ❯

data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch More ❯

data science methodologies Your Background 3+ years of industry experience as a Data Scientist , plus a strong academic foundation Python Data Science Stack : Advanced proficiency in Python , including Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch More ❯

Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression More ❯

ideas with the wider team, learn from and contribute to the body of knowledge. Key Skills Experience using Python and SQL. Strong proficiency with data manipulation including packages like NumPy, Pandas. Knowledge of machine learning techniques and their respective pros and cons. Confident communicator and contributes effectively within a team environment. Self driven and willing to lead on projects/ More ❯

and graph analytics and hands on experience 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 business goals. Experience with big More ❯

environment where research rapidly turns into real-world applications No domain expertise required — curiosity and adaptability are key Technical skillset: Must-have: Python, data science/ML libraries (pandas, NumPy, scikit-learn, XGBoost, PyTorch, Hugging Face), experiment design, evaluation metrics Nice-to-have: LLM fine-tuning, prompt engineering, SQL/PostgreSQL How We Work We live for our customers — aiming More ❯

environment where research rapidly turns into real-world applications No domain expertise required — curiosity and adaptability are key Technical skillset: Must-have: Python, data science/ML libraries (pandas, NumPy, scikit-learn, XGBoost, PyTorch, Hugging Face), experiment design, evaluation metrics Nice-to-have: LLM fine-tuning, prompt engineering, SQL/PostgreSQL How We Work We live for our customers — aiming More ❯

language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and trade More ❯

language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and trade More ❯

language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and trade More ❯

or C# , ensuring scalability and performance. Implement and manage ETL (Extract, Transform, Load) processes to support data integration and transformation workflows. Utilize Python data processing libraries such as pandas , NumPy , or PySpark to handle large datasets efficiently. Lead technical design discussions and mentor junior developers. DevOps & Infrastructure Design and implement CI/CD pipelines using GitHub Actions, Jenkins, or similar … ML integration and data-driven orchestration frameworks. Experience with ETL processes and SQL Server Integration Services (SSIS) is highly beneficial. Proficiency with Python data processing libraries such as pandas, NumPy, or PySpark is considered a strong asset. Nice to have: experience building and deploying UI frameworks like React or Angular. The Person: Strong interpersonal skills to work effectively with PMO More ❯