25 of 25 Pandas Jobs in Berkshire

Snowflake, AWS, and Python Work directly with investment professionals to scope and deliver solutions What we’re looking for: Strong Python engineering skills, including use of data libraries like pandas and NumPy Experience working in front office environments Familiarity with data pipelines and cloud infrastructure Pragmatic, detail-oriented, and able to work independently Experienced Python-focused Software/Data Engineer More ❯

a bonus but not mandatory Desired Skills and Experience: Kafka and message bus/queue expertise Terraform and GitHub Actions skills Open Telemetry (OTEL) implementation Proficiency with NumPy and Pandas Systems integration experience Background in commodity trading (gas & power) Quantitative finance knowledge Understanding of compliance and regulation, particularly Sarbanes-Oxley (SOx) Role Responsibilities: Collaborate with both technical and business stakeholders More ❯

Python Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced 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 ❯

years in a leadership or senior role. Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data stack tools (e.g. More ❯

and iterate on solutions. Requirements 1-4 years of experience in a quantitative, analytics, or developer role within a financial institution or trading environment. Strong proficiency in Python (e.g., Pandas, NumPy, Jupyter) and experience building data pipelines , analytical tools , or dashboards . SQL experience is a plus. Proficiency in Excel and data visualization platforms such as Power BI, Tableau, or More ❯

years of professional software development with exposure to capital markets or trading (equities and/or execution). Technical Skills: Proficient in Python with some exposure to data analysis (Pandas, NumPy) or similar (R, MATLAB). Solid background in object-oriented programming (Java preferred; C++ or C# also valued). Familiarity with Linux-based systems (configuration, scripting, deployment). Docker More ❯

Experience in both data engineering 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, and data modeling. Familiarity with More ❯

approaches. Deployment: ship a model as a container, update an Airflow (or Azure Data Factory) job. Review: inspect dashboards, compare control vs. treatment, plan next experiment. Tech stack Python (pandas, NumPy, scikit-learn, PyTorch/TensorFlow) SQL (Redshift, Snowflake or similar) AWS SageMaker → Azure ML migration, with Docker, Git, Terraform, Airflow/ADF Optional extras: Spark, Databricks, Kubernetes. What you … yrs optimisation/recommender work at production scale (dynamic pricing, yield, marketplace matching). Mathematical optimisation know-how - LP/MIP, heuristics, constraint tuning, objective-function design. Python toolbox: pandas, NumPy, scikit-learn, PyTorch/TensorFlow; clean, tested code. Cloud ML: hands-on with AWS SageMaker plus exposure to Azure ML; Docker, Git, CI/CD, Terraform. SQL mastery for More ❯

Integer Programming (MILP, MIQP, MIQCP). Proficient with Gurobi Optimizer (or equivalent like CPLEX, CBC). Understanding of electricity system balancing, dispatch processes, and control systems. Python ecosystem (NumPy, Pandas, SciPy, Pyomo, etc.) Gurobi Optimizer (for LP, QP, MILP, etc.) Contract Details: Duration: 6 months (View for Extension) Day Rate: Up to £500 per day (Inside IR35) Location: Hybrid 3x More ❯

Python. Python Development: Develop and maintain Python code for data processing, API development, and integration with the Azure Databricks environment. Utilise relevant Python libraries and frameworks (e.g., Flask, Django, Pandas, NumPy). Collaborate with cross-functional teams to build and enhance banking applications. Work closely with UI/UX Designers to integrate visualizations seamlessly into web applications or other platforms. More ❯

a related field. 3+ years of experience as a Quant Developer or in a similar role. Strong programming skills in Python and C++. Experience with Python data science tools (Pandas, Numpy, Scikit-learn). Exceptional coding, debugging, and analytical abilities. Strong problem-solving and communication skills. Ownership mentality with the ability to multitask effectively. Commitment to writing clean, well-tested More ❯

s or PhD degree in a quantitative field. • Proven experience of large-scale data analysis and hypothesis testing. • Strong proficiency in statistical analysis and predictive modeling. • Proficient in Python (pandas, scipy, numpy, scikit-learn) or R (tidyverse/data.table), along with SQL. • Excellent problem-solving skills and attention to detail. • Strong communication skills with the ability to present complex data More ❯

in statistics and machine learning to real world commercial problems Experience bringing live services using machine learning and python to production. Expert knowledge of Python and relevant libraries (numpy, pandas, matplotlib, Scikit-learn, tensorflow, etc...) knowledge in other programming languages is valuable, but this is primarily a Python shop. Experience with things like CI/CD pipelines, Docker or similar More ❯

A/B tests on incentives and matching logic; recommend refinements. Turn insights into pricing rules, contract tweaks and product changes alongside Commercial, Product and Engineering. Tech toolkit Python (pandas, NumPy, scikit-learn) · SQL · Azure (migration in flight) · BI (Power BI/Tableau useful). Ideal background 3-5 yrs (Minimum) analytics in trading, marketplace, media or e-commerce settings. … and propose smarter approaches. Desired Skills and Experience Key experience & expertise 3-5 yrs analytics in high-volume trading, marketplace, media or e-commerce settings Advanced SQL + Python (pandas, NumPy, scikit-learn) for large-scale data wrangling & modelling Hands-on pricing/yield optimisation and causal analysis (regression, clustering, uplift) Cloud data workflows on AWS or Azure (preferably mid More ❯

Designing Generative AI Proof of Concept. Contributing to AI infrastructure. Building reliable, scalable, and flexible systems. Influencing opinion and decision-making across AI and ML. Skills Python SQL/Pandas/Snowflake/Elasticsearch Airflow/Spark Familiarity with GenAI models/libraries Requirements 6+ years of relevant software engineering experience post-graduation. A degree (ideally a Master’s) in More ❯

work with the latest technology on highly visible, large-scale projects. What you'll bring to the role Strong grounding in ML approaches, techniques, and frameworks Proficiency in Python, Pandas, TensorFlow, Scikit-learn, Numpy, SciPy Experience deploying models to the cloud and working with Azure (Azure DevOps, Azure ML, Azure SQL, ADF, etc.) Ability to work with databases such as More ❯

Mathematics, or Engineering. 5+ years of experience in data science, with strong proficiency in writing scale and production-grade code in Python. Solid understanding and proficiency in working with Pandas, NumPy, Scikit-Learn, TensorFlow, and PyTorch, SQL. Proficiency in advanced data visualization tools and libraries (e.g., Matplotlib, Seaborn, Plotly, Tableau) for creating insightful and interactive visualizations. Solid understanding of data More ❯

Statistics, Engineering). 3+ years of professional experience in Data Science or Quantitative roles within finance. Proficiency in Python and SQL with exp. in data processing libraries such as pandas/numpy. Experience with machine learning frameworks and statistical analysis tools. Familiarity with financial data sources, APIs, and data modelling techniques. Ability to design, implement, and maintain scalable data pipelines More ❯

Database Proficiency: Strong hands-on experience with Oracle, SQL Server, and PostGres SQL databases. Technical Skills: Proficiency in at least 2 of the following: SQL, PSQL, C#, Python and Pandas for data manipulation and analysis. Problem Solving: Detail-oriented with exceptional problem-solving skills, capable of troubleshooting issues quickly and efficiently. Communication: Excellent ability to convey technical concepts to non More ❯

the Product organization, you will work with product managers and engineers to explore product innovations arising from emerging technologies and new customer use cases. Technology You'll Use Python, pandas, PyTorch, Databricks, Snowflake, AWS Bedrock, SageMaker, Azure ML, Google Vertex AI Your Role Responsibilities Research and develop expertise in product innovation areas including unstructured data management, AI governance, and protected … approaches to find the best fit for use cases. Effective technical communication skills to advocate solutions and explain them clearly to non-experts. Proficiency in Python, including libraries like pandas, PyTorch, matplotlib, and Seaborn, with experience in data science and engineering. Experience with cloud service technologies and enterprise tools such as Databricks, Snowflake, AWS Bedrock, SageMaker, Azure ML, and Google More ❯

experience in machine learning applications such as recommendations, segmentation, forecasting, and marketing spend optimisation. Proficiency in Python, SQL, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, and PyTorch. Expertise in cloud platforms (AWS, Databricks, Snowflake) and containerisation tools (Docker, Kubernetes). Strong leadership skills with experience mentoring and managing data science teams. Deep knowledge of media More ❯

Data Science, with a proven track record of delivering impactful projects. Strong statistical and machine learning expertise, with the ability to apply and evaluate various algorithms. Proficiency in Python (Pandas), SQL, and data analytics tools. Experience deploying and evaluating ML models in production environments. Ability to interpret complex datasets, drawing meaningful insights to drive business decisions. Strong communication skills, with More ❯

robustness, interpretability, and business relevance. Requirements Extensive experience in building and deploying Marketing Mix Models, with a strong focus on Bayesian methods. Expert-level proficiency in Python, especially with pandas, NumPy, and probabilistic programming libraries such as PyMC. Experience with R is a bonus, particularly for MMM-related workflows. Deep understanding of regression modelling, Bayesian inference, hierarchical models, and MCMC More ❯

experience building machine learning models for marketing use cases ADVANCED skills in segmentation, recommendation, campaign optimisation, forecasting, etc. Proficiency in Python, SQL, Bash, and Git. Familiarity with tools like Pandas, Jupyter notebooks, PyTorch. Experience with advanced techniques including CausalAI, NLP, RNNs, GraphAI, GenAI, and Computer Vision. Solid understanding of experimentation methods including A/B testing. Strong communication skills and More ❯