51 to 70 of 70 Pandas Jobs in London

. Utilise SQL for data extraction, transformation, and analysis. Skills & Experience Proven experience working as a Pricing Analyst. Strong proficiency in SQL and Python (including data libraries such as pandas, NumPy, scikit-learn, etc.) Skilled in Power BI or equivalent visualisation platforms. Background in retail, ticketing, or loyalty environments preferred. Experience in clustering, segmentation, and data modelling. Location: Shepherds Bush More ❯

innovative language assessments and predictive models. Optimize models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. Strategic thinking around architecture and More ❯

research and insights. What we're looking for: Strong hands-on experience with time-series modelling (ARIMA, VAR, GARCH, Prophet, LSTMs, Transformers, etc.). Proficiency in the Python ecosystem (pandas, scikit-learn, statsmodels, PyTorch/TensorFlow; polars/dask a plus). Familiarity with SQL and handling large datasets. Curiosity and interest in financial markets and macroeconomics . Master's More ❯

across EMEA to drive productivity and efficiency. Own sales operations functions including pipeline management, incentive compensation, deal desk, lead management, and contact centre operations . Use SQL and Python (Pandas, PySpark) to analyse data, automate workflows, and generate insights. Design and manage ETL/ELT processes, data models, and reporting automation . Leverage Databricks, Snowflake, and GCP to enable scalable More ❯

Skills & Experience Current enhanced DV clearance (mandatory) Proven experience in a data science or machine learning role Strong programming skills in Python and familiarity with key data libraries (e.g. pandas, NumPy, scikit-learn) Experience with data wrangling , feature engineering, and model optimisation Understanding of data pipelines , APIs, and production deployment workflows Excellent communication skills and a collaborative approach Why Apply More ❯

Experience: Proven experience working as a Data Scientist or Machine Learning Engineer in a commercial setting. Strong programming skills in Python, with hands-on experience using libraries such as Pandas, Scikit-Learn, Jupyter, and Matplotlib. Proficient in SQL for data extraction and transformation. Experience with Google Cloud Platform (GCP) and Vertex AI for developing and deploying ML services is highly More ❯

Data Scientist, your background will include: 3+ years industry experience in a Data Science role and a strong academic background Python Data Science Stack: Advanced proficiency in Python , including pandas , NumPy , scikit-learn , and Jupyter Notebooks . Statistical & ML Modelling: Strong foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g. More ❯

degree in a quantitative field (e.g. Statistics, Mathematics, Physics, Machine Learning) You're confident in Python (production-level) and SQL, and at home with modern ML libraries such as Pandas, scikit-learn, and TensorFlow You have practical experience with MLOps frameworks and deploying models You're skilled at bringing data to life through visualisation, and tools like Tableau feel natural More ❯

industry experience, or an MS with significant industry or research experience in the field • Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) • Ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals • Experience with big data and scalable model More ❯

to solve business problems Proven experience in translating technical methods to non-technical stakeholders Strong programming experience in python (R, Python, C++ optional) and the relevant analytics libraries (e.g., pandas, numpy, matplotlib, scikit-learn, statsmodels, pymc, pytorch/tf/keras, langchain) Experience with version control (GitHub) ML experience with causality, Bayesian statistics & optimization, survival analysis, design of experiments, longitudinal More ❯

and have in-depth knowledge of how they work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn Tooling & Environment : DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker Cloud: You have worked More ❯

databases and dashboarding software such as Power BI or Tableau is important. Familiarity with programming languages such as Python or R and their associated data analysis libraries (e.g., NumPy, Pandas, scikit-learn) is a plus. Statistical Expertise: Strong understanding of statistics, including descriptive statistics, regression, probability, sampling, and hypothesis testing. Communication: Excellent written and verbal presentation skills, with the ability More ❯

general usage, API implementation, and prompt construction Strong Excel proficiency, including formulas such as VLOOKUPs and handling large datasets Skilled in coding using Python, with experience in data analysis (Pandas), API integration, and preferably web scraping (Beautiful Soup 4, Selenium, Playwright, Requests) Nice to have, but not essential experience would be - SQL experience, including writing and optimising queries and/ More ❯

Strong fundamentals in software engineering: testing, version control, CI/CD, clean architecture Passion for building internal tools, research frameworks, or working on data-heavy systems Bonus: Exposure to pandas, NumPy, asyncio, Cython, or PyArrow. Familiarity with C++ is a plus Bonus++: Experience working with quants, data scientists, or in trading environments Tech Stack: Python 3.11+ (fast, modern, typed) Dask … pandas, PyArrow, NumPy PostgreSQL, Parquet, S3 Airflow, Docker, Kubernetes, GitLab CI Internal frameworks built for scale and speed Why Join: Engineers own projects end-to-end—from design to deployment to impact Work side-by-side with quants, traders, and researchers in a flat, fast-moving team Competitive compensation at the top of the market, with research-aligned bonuses No More ❯

secure, scalable, and maintainable applications using Python and Azure cloud technologies for commodities trading solutions. Leverage strong proficiency in Python, including use of numerical and scientific libraries such as Pandas, NumPy, SciPy etc. Utilize a second strongly typed programming language (e.g., C#, C++, Rust, or Java) as needed. Implement application architecture and DevOps best practices, including Infrastructure as code, Kubernetes … requirements into technical specifications and software products. Mandatory Skills Extensive experience in Python application development, especially within trading, finance, or quantitative domains. Proficiency with major Python numerical libraries (e.g., pandas, numpy, scipy, stats). Experience with at least one additional strongly typed programming language (C#, C++, Rust, Java, etc.). Strong background in Azure cloud application development, including security, observability More ❯

secure, scalable, and maintainable applications using Python and Azure cloud technologies for commodities trading solutions. Leverage strong proficiency in Python, including use of numerical and scientific libraries such as Pandas, NumPy, SciPy etc. Utilize a second strongly typed programming language (e.g., C#, C++, Rust, or Java) as needed. Implement application architecture and DevOps best practices, including “Infrastructure as code”, Kubernetes … requirements into technical specifications and software products. Mandatory Skills Extensive experience in Python application development, especially within trading, finance, or quantitative domains. Proficiency with major Python numerical libraries (e.g., pandas, numpy, scipy, stats). Experience with at least one additional strongly typed programming language (C#, C++, Rust, Java, etc.). Strong background in Azure cloud application development, including security, observability More ❯

with Front Office stakeholders and datasets, particularly within FICC asset classes Qualifications Essential skills: Proficiency in Python: Solid experience writing clean, efficient, and scalable Python code. Data Manipulation with Pandas: Strong understanding of data frames, data cleaning, transformation, and analysis using the Pandas library. Software Development Life Cycle (SDLC): Demonstrated experience working across all phases of the SDLC, including requirements More ❯

tools, and data pipelines to assist portfolio managers in making informed investment decisions. The ideal candidate will be proficient in Python and have experience working with data structures like Pandas to build scalable and efficient solutions in a fast-paced, dynamic environment. Responsibilities Collaborate closely with equity portfolio managers to understand their needs and develop software solutions to enhance portfolio … to analyze large datasets and derive actionable insights for equity portfolios. Build and maintain data pipelines, ensuring data accuracy, reliability, and scalability. Use Python (and related libraries such as Pandas, NumPy, etc.) to develop and automate tasks, backtest strategies, and optimize performance. Work with portfolio managers to create tools for portfolio construction, risk analysis, and scenario modeling. Ensure seamless integration … Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Finance, or a related field. Strong proficiency in Python, with a deep understanding of libraries like Pandas, NumPy, and others for data manipulation and analysis. Solid understanding of financial markets, particularly equities, and portfolio management concepts. Knowledge of databases (SQL, NoSQL) and experience in working with large More ❯

tools, and data pipelines to assist portfolio managers in making informed investment decisions. The ideal candidate will be proficient in Python and have experience working with data structures like Pandas to build scalable and efficient solutions in a fast-paced, dynamic environment. Responsibilities Collaborate closely with equity portfolio managers to understand their needs and develop software solutions to enhance portfolio … to analyze large datasets and derive actionable insights for equity portfolios. Build and maintain data pipelines, ensuring data accuracy, reliability, and scalability. Use Python (and related libraries such as Pandas, NumPy, etc.) to develop and automate tasks, backtest strategies, and optimize performance. Work with portfolio managers to create tools for portfolio construction, risk analysis, and scenario modeling. Ensure seamless integration … Qualifications Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, Physics, Finance, or a related field. Strong proficiency in Python, with a deep understanding of libraries like Pandas, NumPy, and others for data manipulation and analysis. Solid understanding of financial markets, particularly equities, and portfolio management concepts. Knowledge of databases (SQL, NoSQL) and experience in working with large More ❯

About the roleWe are excited to be hiring a new Data Scientist into our team! Lendable is the market leader in real rate risk-based pricing, offering consumers transparency and product assurance at the point of application. Data Science sits More ❯