26 to 50 of 777 Pandas Jobs in the UK

knowledge of general financial products and derivatives. Understanding of market microstructure. Strong skills in Excel and Python, SQL and time-series databases. Strong familiarity with Agile processes. Experience with Pandas, NumPy, Matlab, R or other mathematical/statistical languages/packages. Experience in leadership and mentoring. Excellent communication skills, both written and spoken. COMPETENCIES Communication Team work Customer focus Resilience More ❯

strong expertise in modern C++20. Deep knowledge of performance optimization techniques, multi-threading, parallel processing, and efficient network utilization. Familiarity with Python and scientific libraries such as NumPy and Pandas (expertise not mandatory). Experience or strong interest in high-performance and big data systems, including data lakes or serverless architectures. A passion for writing clean, efficient, maintainable code and More ❯

Preferred Qualifications, Capabilities, and Skills Experience with FIX protocol, Market Data, Analytics, and OMS. Knowledge of market microstructure. Knowledge of equities, FX, options, and derivatives. Skills in Jupyter/Pandas, KDB+/Q, Python, and shell scripting. About Us J.P. Morgan is a global leader in financial services, providing strategic advice and products to prominent clients worldwide. We prioritize building More ❯

of a degree in Statistics, Applied Maths, Physics or related field. Minimum of 2 years working in a Data Science related role Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt More ❯

on practical experience in system design, application development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming and database querying. Overall knowledge of the Software Development Life Cycle. More ❯

or interest in mentoring junior engineers. Familiarity with data-centric workflows and pipeline orchestration (e.g., Apache Airflow). Proficiency in data validation, anomaly detection, or debugging using tools like Pandas, Polars, or data.table/R. Experience working with AWS or other cloud platforms. Knowledge of building and monitoring high-performance, concurrent services. Additional Information We offer a Friends of Voleon More ❯

numerical methods. Experience with models like regression, tree-based models, support vector machines, PCA, clustering, matrix factorization, deep learning, etc. Proficiency in Python and its machine learning ecosystem (Numpy, Pandas, Scikit-learn, LightGBM, PyTorch). Knowledge of SQL and experience with relational databases. Agile, action-oriented mindset. Nice to Have Experience with Apache Spark, cloud platforms (AWS, GCP, Azure), or More ❯

Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt More ❯

Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt More ❯

Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt More ❯

on practical experience in system design, application development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages. Overall knowledge of the Software Development More ❯

interfaces for interaction with the models Testing and documentation Requirements: Experienced Python developer Experience utilising machine learning libraries such as (in order of importance) TensorFlow, HuggingFace, scikit-learn, PyTorch, Pandas, NumPy, SciPy Experience with AWS (principally EC2, S3, SageMaker) or Azure/GCP equivalents Some experience of designing, developing and deploying scalable infrastructure (eg Apache Airflow, Luigi or other cluster More ❯

Experience or interest in mentoring junior engineers Familiarity with data-centric workflows and pipeline orchestration (e.g., Apache Airflow) Proficiency in data validation, anomaly detection, or debugging using tools like Pandas, Polars, data.table/R Experience working with AWS or other cloud platforms Knowledge of building and monitoring high-performance, concurrent services “Friends of Voleon” Candidate Referral Program If you have More ❯

These are ourvaluesand influence everything we do. Preferred Qualifications Familiarity building scalable services in a microservices architecture. Familiarity with statistical tools such as SAS, or Python (with NumPy, SciPy, Pandas) Familiarity with public cloud platforms, such as AWS, Azure, or GCP. Strong testing automation experience, preferably in *unit frameworks Diverse and Inclusive At SAS, it’s not about fitting into More ❯

Python as a priority Development and maintenance of Continuous Integration (CI) pipelines Complex deployments on AWS Docker or comparable containerization technologies Nice to have experience: Experience using numpy/pandas/torch/etc Experience with Golang Benefits Our salary range for the role is £70,000 to £130,000, depending on experience and interview performance. List of benefits: Participation More ❯

both written and verbal Bonus Points: Experience of research and backtesting to evaluate the performance of trading strategies and models Proficiency in Rust and Python, statistical tools (e.g., NumPy, pandas, SciPy) Experience of development with relational and time series database technologies Knowledge of risk management infrastructure What We Offer: Competitive base salary and discretionary bonus Company-paid health and protective More ❯

software engineering and development, and a strong understanding of computer systems and how they operate. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualization and API libraries (matplotlib, plotly, streamlit, Flask, etc). Experience developing and implementing quantitative models from data in More ❯

methodologies for analyzing and interpreting large datasets. Ability to apply statistical techniques to validate models and algorithms. Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience Equity : Generous equity package, on More ❯

Background of working in hedge fund or alternative investment environment, working directly with investment team on tech delivery is preferrable Understanding of Python, with libraries/frameworks such as Pandas, NumPy, and PySpark. Understanding of distributed computing, with experience using frameworks like Databricks. Experience with Azure or other cloud platforms (AWS) Experience building data pipelines or ETL tools and Orchestration More ❯

and innovative as technology and client needs shift. Role Requirements Technical Skills Substantial experience in data engineering, analytics engineering, or similar roles. Hands-on expertise with Python (Numpy/Pandas) and SQL. Proven experience designing and building robust ETL/ELT pipelines (dbt, Airflow). Strong knowledge of data pipelining, schema design, and cloud platforms (e.g., Snowflake, AWS). Excellent More ❯

using tools such as MLflow, AWS Sagemaker, and Azure Machine Learning Experience in relevant Data Manipulation, Machine Learning and Statistical Analysis coding packages (eg. in Python: NumPy, Scikit-Learn, Pandas, Matplotlib etc.) Strong skills in data exploration, cleansing, modelling and presentation Strong experience in testing data models and Machine Learning Models Strong experience in data presentation and visualisation Desirable Technical More ❯

Fact and Dimension tables in Target D/W Hands-on experience with No-SQL DB, preferably MongoDB. Experience creating reusable code/scripts for Automated Framework using Python (Pandas, Numpy, Requests, Boto3) Experience creating automation frameworks using Selenium (Python) and tools to support test automation for web applications Experience working with Postman, SOAPUI, GraphQL or similar API testing tools More ❯

approaches and frameworks such as RAG, LangChain, TensorFlow, and PyTorch. Exposure to LLMs from model families such as Anthropic, Meta, Amazon, and OpenAI. Familiarity with tools and packages like Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks. Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Proficiency in data pre-processing, data wrangling, and augmentation techniques. More ❯

growing organisation. Role Requirements Technical Expertise 4+ years of experience in analytics engineering, data engineering, or similar roles with substantial experience building production data pipelines Advanced Python skills (NumPy, Pandas, SQL Alchemy) and expert-level SQL across multiple database platforms Hands-on experience with modern data stack tools including dbt, Airflow, and cloud data warehouses (Snowflake, BigQuery, Redshift) Strong understanding More ❯

/NiFi Familiarity with data visualization tools e.g. PowerBI or Tableau Data extraction and manipulation languages e.g. SQL, Python Knowledge of statistical software and packages such as R, Matlab, Pandas, NumPy or SciPy Experience with algorithmic trading systems and low-latency trading Knowledge of financial markets is desirable but experience of working in other "big data" or HPC environments is More ❯