76 to 100 of 328 Pandas Jobs in England

a data product company Experience building or maintaining third-party or in-house data quality and cataloguing solutions Experience with documentation of system architecture Pandas, Jupyter, Plotly DBT, Kafka BI tools such as Tableau, Metabase and Superset The current tech stack: Airflow Clickhouse DBT Python MongoDB PostgreSQL MariaDB Kafka K8s More ❯

FX markets - over the last 3-5 years - in an investment context. Fluent in Python 3.11+, the standard library, and external libraries like numpy, pandas, matplotlib, and scikit-learn. Confident in SQL Server or similar; experience with Azure and Docker is a positive. An understanding of machine learning processes and More ❯

and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL More ❯

and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL More ❯

such as recommendation engines or automated lead scoring systems. They should also be able to perform statistical analysis. Requirements Python for DS (the usuals pandas plotting etc) Modelling skills for both ML applications and data reporting SQL at least basics but by year 3 should be quite proficient with at More ❯

ideation to deployment. Be on-call for urgent AI model fixes or system failures. Qualifications Proficiency in Python and related libraries (e.g., NumPy, SciPy, pandas) is required. Strong production experience with at least one framework: LangChain, AutoGen, or CrewAI. Deep understanding of agentic systems, autonomous workflows, and LLM-based automation. More ❯

skills and a good understanding of software engineering principles and clean code practices. Expert-level knowledge of Python for machine learning and data manipulation (pandas, NumPy). Advanced experience with SQL for data querying and manipulation. Experience with Git, Bash, Docker, and machine learning pipelines. Experience with open-source machine More ❯

Data Science, Computer Science, Statistics, Mathematics, or related fields (PhD a plus) Strong programming skills in Python, with proficiency in data science libraries (NumPy, Pandas, scikit-learn) Experience with SQL for data querying and analysis Solid understanding of machine learning algorithms, statistical methods, and predictive modeling Experience with NLP techniques More ❯

Data Science, Computer Science, Statistics, Mathematics, or related fields (PhD a plus) Strong programming skills in Python, with proficiency in data science libraries (NumPy, Pandas, scikit-learn) Experience with SQL for data querying and analysis Solid understanding of machine learning algorithms, statistical methods, and predictive modeling Experience with NLP techniques More ❯

to mentor colleagues, drive projects forward, and influence stakeholders. You should apply if you: Have a strong technical background, including proficiency in Python (NumPy, Pandas, Scikit-Learn, etc.), SQL, and cloud platforms such as GCP or AWS. Have experience working with modern databases like BigQuery, Snowflake, or Redshift. Have successfully More ❯

to mentor colleagues, drive projects forward, and influence stakeholders. You should apply if you: Have a strong technical background, including proficiency in Python (NumPy, Pandas, Scikit-Learn, etc.), SQL, and cloud platforms such as GCP or AWS. Have experience working with modern databases like BigQuery, Snowflake, or Redshift. Have successfully More ❯

blend of some of the following skills: Machine learning techniques - including supervised and unsupervised methods and model evaluation. Key libraries including scikit-learn, scipy, pandas, and numpy (or equivalents). Data preprocessing - working with large untidy datasets and the ability to clean and transform data in preparation for analysis or More ❯

blend of some of the following skills: Machine learning techniques – including supervised and unsupervised methods and model evaluation. Key libraries including scikit-learn, scipy, pandas, and numpy (or equivalents). Data preprocessing – working with large untidy datasets and the ability to clean and transform data in preparation for analysis or More ❯

blend of some of the following skills: Machine learning techniques – including supervised and unsupervised methods and model evaluation. Key libraries including scikit-learn, scipy, pandas, and numpy (or equivalents). Data preprocessing – working with large untidy datasets and the ability to clean and transform data in preparation for analysis or More ❯

e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for AI model More ❯

e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing: Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for AI model More ❯

control systems (e.g., Git). Strong expertise in Python, with a particular focus on libraries and tools commonly used in data engineering, such as Pandas, NumPy, Apache Airflow. Experience with data pipelines, ELT/ETL processes, and data wrangling. Dashboard analytics (PowerBI, Looker Studio or Tableau) experience. Excellent English, written More ❯

Adobe Substantial experience with data warehouse platforms like Snowflake Substantial experience with languages like SQL, Python Substantial experience with python libraries such as NumPy, Pandas, SciPy, scikit-learn Applied knowledge of machine learning/statistical modelling techniques Experience in using a tag management system like TealiumIQ Knowledge of software development More ❯

IT Experience IT qualification or relevant experience is desirable Proven experience with Python, SQL and desirably SOQL. Familiarity with a base set of libraries (Pandas, Numpy, Scikit-learn etc) Experience with Apex or Java A strong broad generalist background in working with computers and dealing with large amounts of information. More ❯

IT Experience IT qualification or relevant experience is desirable Proven experience with Python, SQL and desirably SOQL. Familiarity with a base set of libraries (Pandas, Numpy, Scikit-learn etc) Experience with Apex or Java A strong broad generalist background in working with computers and dealing with large amounts of information. More ❯

IT Experience IT qualification or relevant experience is desirable Proven experience with Python, SQL and desirably SOQL. Familiarity with a base set of libraries (Pandas, Numpy, Scikit-learn etc) Experience with Apex or Java A strong broad generalist background in working with computers and dealing with large amounts of information. More ❯

complex issues Beneficial experience • Experience in trading or execution roles • Experience with equity/credit markets • Research using large, messy datasets • Familiarity with Linux • Pandas Benefits: Working alongside other extremely talented and driven engineers Extremely lucrative salary, bonus and benefits More ❯

markets Experience with testing methodologies such as TDD (Test-Driven Development) and BDD (Behavior-Driven Development) Familiarity with technologies including PostgreSQL, Jenkins, Django, and Pandas Understanding of Microservices Architecture and development of RESTful API services Exposure to event-driven architectures, message queues, or event-streaming platforms Experience with cloud technologies More ❯

markets Experience with testing methodologies such as TDD (Test-Driven Development) and BDD (Behavior-Driven Development) Familiarity with technologies including PostgreSQL, Jenkins, Django, and Pandas Understanding of Microservices Architecture and development of RESTful API services Exposure to event-driven architectures, message queues, or event-streaming platforms Experience with cloud technologies More ❯

data products. Tech Stack: Python - Core language for geospatial data processing Rasterio/GDAL - For handling and processing raster datasets xarray/NumPy/Pandas - For data manipulation and analysis AWS - For cloud-based data storage and processing PostGIS - For spatial data management (nice to have) What you'll be More ❯