1 to 25 of 322 Pandas Jobs in England

their potential impact on products. Key Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure ...

their potential impact on products. Key Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch).Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure ...

their potential impact on products. Key Skills & Experience: Experience in machine learning, data science, or applied AI roles. Proficiency in Python and ML libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Strong understanding of statistics, ML algorithms, and model evaluation techniques. Experience working with cloud platforms (AWS, Azure ...

scientists, and product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience building data pipelines and working with structured and unstructured data Solid understanding of SQL and relational and non-relational databases ...

world problems. Experience of coaching junior data scientists/analysts. Experience in reviewing code and documentation to a high standard. Experience in using Python (pandas, numpy, scikit-learn). End-to-end experience of managing multiple data science and analytics projects in different industries and with different types of data ...

data warehouses, lakehouse environments or analytics tools such as Power BI. Familiarity with modern data engineering frameworks and tools (e.g. Spark/PySpark, Pandas, orchestration tools). Experience with cloud data platforms on AWS or Azure (e.g. Databricks, Redshift, Microsoft Fabric). Understanding of software engineering fundamentals, including Git, testing ...

principles. Experience with cloud platforms (AWS, Google Cloud, Azure) and containerization technologies (Docker, Kubernetes). Familiarity with databases (SQL, NoSQL) and data processing tools (Pandas, NumPy). Soft Skills Excellent problem-solving skills. Strong communication abilities. Capability to work collaboratively in a team environment. Preferred Skills Experience with natural language ...

DynamoDB, DocumentDB, MongoDB. Demonstrated expertise in unit testing and tools such as JUnit, Mockito, PyTest, and Selenium. Strong working knowledge of the PyData stack—pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation, and experience with data analysis and troubleshooting data‐related issues. Knowledge ...

pipelines in a professional setting (e.g., internship) is a plusAbility to write clean, maintainable, scalable, and robust code in PythonFamiliarity with analytics libraries (e.g., pandas, numpy, matplotlib), distributed computing frameworks (e.g., Spark, Dask), and cloud platforms (e.g., AWS, Azure, GCP)Basic understanding or exposure to containerization technologies such as Docker ...

integer programming, heuristics) Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit‐learn, pandas, numpy, gurobi, etc.) to solve real‐life problems and visualise the outcomes (e.g., seaborn) Proficient in working with cloud platforms (AWS preferred), code versioning ...

scientists, and product managers Contribute to a culture of continuous improvement, knowledge sharing, and technical excellence Required Skills & Qualifications Strong proficiency in Python (NumPy, Pandas, Scikit-learn, or similar) Experience with React (hooks, state management, component architecture) Experience building data pipelines and working with structured and unstructured data Solid understanding ...

more of the following technological areas: Analytics & Platform Frameworks Orchestration like Airflow or AWS Glue Database Technologies Data processing libraries & Schema Management tools like Pandas and Pydantic Storage Formats: Familiarity with data types such as JSON and Parquet DevOps and DataOps Experience of IaC tools, particularly Terraform Understanding of implementing ...

more of the following technological areas: Analytics & Platform Frameworks Orchestration like Airflow or AWS Glue Database Technologies Data processing libraries & Schema Management tools like Pandas and Pydantic Storage Formats: Familiarity with data types such as JSON and Parquet DevOps and DataOps Experience of IaC tools, particularly Terraform Understanding of implementing ...

statistical analysis, A/B testing, time-series, regression, classification and optimisation problems. Proficient in SQL & Python. Familiarity with data manipulation libraries (e.g. PySpark, Pandas, Numpy) and machine learning frameworks (e.g. scikit-learn, TensorFlow or PyTorch). Experience with MLOps tools (e.g., MLflow, Databricks Model Registry, Unity Catalog, Vertex ...

skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...

engineering fundamentals: working with Parquet, Hive-partitioned datasets, and SQL against large tables (Athena/Presto). Solid working knowledge of the PyData stack — pandas and NumPy for data manipulation, Jupyter for experimentation, matplotlib/Seaborn for visualisation — and experience troubleshooting data-quality issues. Testing discipline with PyTest ...

translate business problems into measurable analytical outcomes.* Experience taking models from development into production environments.### Technical Skills* Python and associated data science ecosystem (Pandas, NumPy, Scikit-learn).* Machine learning techniques including classification, regression, clustering and anomaly detection.* Experience with Generative AI, LLMs, RAG architectures or agent-based AI solutions. ...

Computer Science, Mathematics, Statistics or another STEM-related discipline. Desirable Skills Experience with cloud platforms such as AWS, Azure or GCP . Experience with Pandas, NumPy and Scikit-learn . Knowledge of data visualisation tools such as Power BI or Tableau. Experience with Git/version control. Exposure to Generative ...

Linux environment Nice to have: Advanced data engineering experience in Python, e.g. with libraries like Dagster, Prefect etc Experience optimising dataframe code, e.g. in Pandas or ideally Polars Experience of machine learning techniques and related libraries and frameworks e.g. scikit-learn, Pytorch, Tensorflow etc Experience deploying and serving ML models ...

Excellent communication skills with the ability to communicate concepts clearly and precisely Experience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure) NICE TO HAVES Experience as a Data Architect or Senior Manager Proven track record ...

sequential modelingExcellent communication skills with the ability to communicate concepts clearly and preciselyExperience writing software using: i) Python for data science (numpy, scipy, scikit, pandas; ii) databases; and iii) cloud platform services (AWS, GCP, Azure)NICE TO HAVESExperience as a Data Architect or Senior ManagerProven track record of deploying ...

analytical outcomes. Desirable Well developed experience in a Lloyd’s syndicate, managing agent, London Market broker or specialty (re)insurer. Python for data analysis (pandas/notebooks) and an appreciation of wider data science techniques, enough to collaborate credibly with Data Scientists and Actuarial. Hands‐on experience applying AI/ ...

from concept through to production. Strong technical knowledge, including proficiency in Python and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow). Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative ...

concept through to production. Strong technical knowledge, including expert-level Python proficiency and experience with core data science and ML libraries (e.g., scikit-learn, pandas, PyTorch or TensorFlow).Practical experience with Databricks, including MLflow for experiment tracking and model management, and Spark-based data processing. Familiarity with Generative AI concepts ...

skills, with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines ...