26 to 50 of 219 Pandas Jobs in England

Strong problem-solving skills and attention to detail. Eagerness to learn about trading systems, low-latency development, and financial markets. Experience with data analytics tools or frameworks (Python, SQL, Pandas, etc.) is advantageous but not essential. A degree in Computer Science, Engineering, or a related field (or equivalent practical experience). Why Join Us Work in a dynamic, high-impact More ❯

Manage cloud-based and on-prem setup Requirements: 25 years experience in ML engineering/MLOps roles Strong proficiency in Python and experience with relevant ML libraries/frameworks (pandas, numpy, sklearn, TensorFlow, PyTorch) Strong understanding and experience in implementing end-to-end ML pipelines (data, training, validation, serving) Experience with ML workflow orchestration tools (e.g., Airflow, Prefect, Kubeflow) and More ❯

scalability of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow More ❯

scalability of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow More ❯

related field. Deep understanding of option pricing theory (Black-Scholes, local/stochastic volatility, Monte Carlo). Expert Python developer with strong numerical and vectorized coding skills (NumPy, SciPy, Pandas). Experience building and calibrating volatility surfaces and handling risk measures (Greeks, VaR, sensitivities). Strong background in stochastic calculus, numerical methods, and optimization. More ❯

related field. Deep understanding of option pricing theory (Black-Scholes, local/stochastic volatility, Monte Carlo). Expert Python developer with strong numerical and vectorized coding skills (NumPy, SciPy, Pandas). Experience building and calibrating volatility surfaces and handling risk measures (Greeks, VaR, sensitivities). Strong background in stochastic calculus, numerical methods, and optimization. More ❯

e.g., Mathematics, Statistics, Computer Science, Engineering, Physics, Economics); advanced degree preferred. Strong expertise in statistical modelling, Bayesian inference, and machine learning. Proficient in Python (using libraries such as NumPy, pandas, scikit-learn, PyMC or Stan) Experienced in SQL. Ability to write efficient and robust queries. Demonstrated experience working with large and complex datasets. Ability to communicate complex analytical concepts clearly More ❯

e.g., Mathematics, Statistics, Computer Science, Engineering, Physics, Economics); advanced degree preferred. Strong expertise in statistical modelling, Bayesian inference, and machine learning. Proficient in Python (using libraries such as NumPy, pandas, scikit-learn, PyMC or Stan) Experienced in SQL. Ability to write efficient and robust queries. Demonstrated experience working with large and complex datasets. Ability to communicate complex analytical concepts clearly More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data streams More ❯

and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data streams More ❯

is required for this role. Essential Skills & Experience: • Proven experience developing solutions with Power Apps (Canvas and Model-driven apps). • Strong proficiency in Python, including libraries such as Pandas, NumPy, and Flask or FastAPI. • Experience with Microsoft Power Platform, including Power Automate and Dataverse. • Ability to mentor and support junior staff in technical development. • Excellent communication and stakeholder engagement More ❯

machine learning, particularly in recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work More ❯

learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP/Azure, Docker, Kubernetes, MLflow More ❯