76 to 100 of 241 Pandas Jobs in the UK

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 ❯

scale up? Having added nearly 100 people to the business this year, they're looking for Quantitative Developers with proficiency in Python, and experience with the Python data libraries (Pandas, NumPy) (preferably) from the Trading world. They also are on the look out for candidates who: Have deep familiarity with Python data ecosystem Understanding of Jupyter notebooks Exposure to machine More ❯

scale up Having added nearly 100 people to the business this year, they're looking for Quantitative Developers with proficiency in Python, and experience with the Python data libraries (Pandas, NumPy) (preferably) from the Trading world. They also are on the look out for candidates who: Have deep familiarity with Python data ecosystem Understanding of Jupyter notebooks Exposure to machine More ❯

Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python programming skills with experience in core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. A More ❯

strategies Provide data-driven recommendations to improve engagement metrics Requirements Experience in Customer Marketing Data Science, including applied statistics and machine learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks Experience with ML Ops, including deployment and monitoring Ability to work cross-functionally More ❯

strategies Provide data-driven recommendations to improve engagement metrics Requirements Experience in Customer Marketing Data Science, including applied statistics and machine learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks Experience with ML Ops, including deployment and monitoring Ability to work cross-functionally More ❯

Analytical mindset with interest in systematic trading and quantitative research Nice to Have Exposure to trading systems, market data, or algo/bot development Familiarity with numerical libraries (NumPy, Pandas, Numba, etc.) Understanding of version control, CI/CD, or distributed computing More ❯

Analytical mindset with interest in systematic trading and quantitative research Nice to Have Exposure to trading systems, market data, or algo/bot development Familiarity with numerical libraries (NumPy, Pandas, Numba, etc.) Understanding of version control, CI/CD, or distributed computing More ❯

up-to-date with emerging trends and technologies in the field of data science. Requirements Proven experience as a data scientist using Python and a range of libraries (Numpy, Pandas, Scikit-Learn, Matplotlib, Plotly etc.). Strong expertise in statistical modelling, machine learning, and data mining techniques. Data engineering (pipelines, databases, infrastructure), ideally with AWS experience would be an advantage. More ❯

deployable AI solutions Key Skills & Experience Required Senior-level experience in data science or a quantitative field Proficient programming skills (Python preferred); familiarity with core data science libraries (NumPy, Pandas, Scikit-Learn) Experience with deep learning tools (e.g. PyTorch, TensorFlow, or similar) Strong mathematical/statistical background Familiarity with a wide range of data science methods (e.g. ML, NLP, Bayesian More ❯

engineering experience, ideally in Treasury or from a hedge fund/buy-side firm Expertise in Python for designing and optimising complex applications Strong proficiency in data tools like Pandas, NumPy, SQL, and real-time data processing Familiarity with DevOps practices, including Linux, cloud platforms, and CI/CD (Docker/Kubernetes is desirable but not essential). Strong communication More ❯

engineering experience, ideally in Treasury or from a hedge fund/buy-side firm Expertise in Python for designing and optimising complex applications Strong proficiency in data tools like Pandas, NumPy, SQL, and real-time data processing Familiarity with DevOps practices, including Linux, cloud platforms, and CI/CD (Docker/Kubernetes is desirable but not essential). Strong communication More ❯

Looking For: Essential: Experience with LLMs (GPT, BERT) and NLP tasks. Fine-tuning pre-trained models for domain-specific applications. Strong Python skills (OOP, PyTorch, Hugging Face, scikit-learn, Pandas, NumPy). Deploying models with Docker, Kubernetes, or serverless platforms. Familiarity with CI/CD, MLOps, and cloud platforms (AWS preferred). Desirable: Named entity recognition, recommendation systems, or image More ❯

Looking For: Essential: Experience with LLMs (GPT, BERT) and NLP tasks. Fine-tuning pre-trained models for domain-specific applications. Strong Python skills (OOP, PyTorch, Hugging Face, scikit-learn, Pandas, NumPy). Deploying models with Docker, Kubernetes, or serverless platforms. Familiarity with CI/CD, MLOps, and cloud platforms (AWS preferred). Desirable: Named entity recognition, recommendation systems, or image More ❯

modern data platforms and cloud technologies. Key Responsibilities: Develop, test, and deploy scalable data engineering solutions using Python . Build and maintain data pipelines leveraging libraries such as NumPy, pandas, BeautifulSoup, Selenium, pdfplumber, and Requests . Write and optimize complex SQL queries and manage databases including PostgreSQL . Integrate and automate workflows using DevOps tools (e.g., CI/CD, Jenkins More ❯

modern data platforms and cloud technologies. Key Responsibilities: Develop, test, and deploy scalable data engineering solutions using Python . Build and maintain data pipelines leveraging libraries such as NumPy, pandas, BeautifulSoup, Selenium, pdfplumber, and Requests . Write and optimize complex SQL queries and manage databases including PostgreSQL . Integrate and automate workflows using DevOps tools (e.g., CI/CD, Jenkins More ❯

education to teams adopting AI tooling. What Youll Bring 5+ years in software/ML engineering, ideally with production deployment experience. Strong Python background, comfortable across data frameworks like Pandas, NumPy, SciPy, Dask, Polars, or PySpark. Proven experience setting up ML pipelines, integrating with AWS/Databricks, and applying CI/CD principles. Solid understanding of time-series forecasting and More ❯

to teams adopting AI tooling. What You’ll Bring • 5+ years in software/ML engineering, ideally with production deployment experience. • Strong Python background, comfortable across data frameworks like Pandas, NumPy, SciPy, Dask, Polars, or PySpark. • Proven experience setting up ML pipelines, integrating with AWS/Databricks, and applying CI/CD principles. • Solid understanding of time-series forecasting and More ❯

analyse and reverse engineer existing stored procedures to extract and understand business logic Federated Data Platform (FDP): Solid Python development experience for data engineering Excellent SQL skills Knowledge of Pandas and/or PySpark General Technical Skills: Git/GitHub and understanding of DevOps practices (CICD, secrets scanning) Experience with cloud-based engineering (Azure/AWS/GCP) Front-end 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 ❯

AI-driven initiatives, including text and sentiment analysis Collaborating closely with Data Engineering and BI to deliver robust, end-to-end ML pipelines and model monitoring Tech Environment: Python (pandas, scikit-learn, modern ML frameworks) SQL for analysis and model input preparation Cloud environment (AWS/GCP/Azure) Exposure to NLP, MLOps, or CI/CD pipelines is a More ❯

and modelling skills, including time series and ensemble models. Experience in manipulating and interpreting data from disparate sources. Proficient in Python coding and core data science libraries, such as Pandas, TensorFlow, Scikit-learn etc. Ideally previous experience with Snowflake and DBT. Experience with Cloud Computing (AWS, GCP, Azure) - Ideally in AWS. Creativity and innovative thinking to explore diverse data sources More ❯

Technical & Analytical Skills Hands-on experience with large data sets and data profiling. Proficiency in data tools: Power BI, Excel, SQL, Python, Databricks. Familiarity with tools like Great Expectations, Pandas, Plotly, or MS Power Automate is a plus. Able to work collaboratively and independently in a fast-paced environment. Ready to Apply? If you're excited by the opportunity to More ❯

Technical & Analytical Skills Hands-on experience with large data sets and data profiling. Proficiency in data tools: Power BI, Excel, SQL, Python, Databricks. Familiarity with tools like Great Expectations, Pandas, Plotly, or MS Power Automate is a plus. Able to work collaboratively and independently in a fast-paced environment. Ready to Apply? If you're excited by the opportunity to More ❯