1 to 25 of 58 Pandas Jobs in the UK excluding London

and more on reliability and fixes. Key Skills: Investigating and debugging complex data flow and Machine Learning issues within a live, high impact production environment. Extensive Python, NumPy and Pandas is required for this role. You must demonstrate a deep commercial background in the following areas: Extensive Python: Very strong, production-level Python coding and debugging skills. Production Environment: Proven 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 ❯

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 ❯

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 ❯

flows and ML issues in live production environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer More ❯

basic AI algorithms and explore practical applications of AI. Overview of AI and Machine Learning Types of machine learning (supervised, unsupervised, reinforcement) Introduction to Python Libraries for AI - NumPy, Pandas, Matplotlib Scikit-learn for machine learning Building AI Models Data preprocessing Training and evaluating models Advanced Programming for AI Integration This programme aims to equip participants with the knowledge and More ❯

neural networks, NLP, etc.). Hands-on experience with frameworks such as TensorFlow , PyTorch , or scikit-learn . Proficiency in Python and familiarity with common data science libraries (NumPy, pandas, etc.). Solid grasp of statistics, linear algebra, and probability. Excellent problem-solving skills and ability to communicate complex ideas clearly. Desirable Skills Experience with deep learning architectures (CNNs, RNNs More ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

data cycle. Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD Coding experience in Apache Spark, Iceberg or Python (Pandas) Experience in change and release management. Experience in Database Warehouse design and data modelling Experience managing Data Migration projects. Cloud data platform development and deployment. Experience of performance tuning in More ❯

data cycle. - Proven Experience working with AWS data technologies (S3, Redshift, Glue, Lambda, Lake formation, Cloud Formation), GitHub, CI/CD - Coding experience in Apache Spark, Iceberg or Python (Pandas) - Experience in change and release management. - Experience in Database Warehouse design and data modelling - Experience managing Data Migration projects. - Cloud data platform development and deployment. - Experience of performance tuning in More ❯

relevant insights Advanced statistical and analytical techniques and concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This is a pragmatic and humble organisation who More ❯

months with possible extensions (No Sponsorship Available ) Skills/Qualifications: · 4+ years of experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc. · 3+ years hands-on experience with cloud services, especially Databricks, for building and managing scalable data pipelines · 3+ years of proficiency in working with Snowflake or similar cloud-based More ❯

predictive model- Clear explainability on what drives user clicks- A functional internal tool for non-technical stakeholders- Documentation and guidance for productionisation Required Skills Must-Have: Expert-level Python (Pandas, modelling libraries such as Scikit-learn) SQL AWS cloud experience Proven end-to-end ownership of data science solutions Model explainability (SHAP, LIME, feature importance) Ability to build simple dashboards More ❯

the latest developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

driven setting? Were looking for a talented OPS Engineer to join our growing teams in Erskine or Newcastle. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML More ❯

technical and non-technical stakeholders. Stay ahead of the curve by experimenting with emerging AI and ML techniques. What You’ll Bring Strong background in Python or R (e.g., Pandas, NumPy, Scikit-learn, TensorFlow). Skilled in SQL and statistical analysis. Proven experience in data science, ideally within energy, optimisation, or IoT-focused applications. Solid grasp of machine learning techniques More ❯

master’s degree in a STEM subject (Mathematics, Computer Science or Engineering) Experience working in a data science or consulting role In-depth experience of working with Python and Pandas An entrepreneurial spirit and drive to work in an early stage start-up A curious mindset to understand how we can improve things and better help our clients address commercial More ❯

in Computer Science, Engineering, or a related field (or equivalent experience). 4+ years of experience developing data pipelines and data warehousing solutions using Python and libraries such as Pandas, NumPy, PySpark, etc. 3+ years hands-on experience with cloud services, especially Databricks, for building and managing scalable data pipelines 3+ years of proficiency in working with Snowflake or similar More ❯

Load Balancing. • CI/CD & DevOps Integration. • AWS (ECS, fargate , EC2, SNS, SQS, Cloudwatch, EKS, Kubernetes). Desirable skills/knowledge/experience: • Familiarity with data analysis libraries like Pandas, NumPy, and Scikit-learn. • Knowledge of data science and machine learning concepts and tools. Good to have: • Strategic thinking and problem-solving. • Collaboration and teamwork. • Effective communication and stakeholder management. More ❯

proofs-of-concept , model monitoring , and adoption of emerging AI tech. What We’re Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving skills. Passion for innovation More ❯