21 of 21 Permanent Pandas Jobs in the Thames Valley

knowledge of machine learning and/or optimisation techniques (Regression, Tree methods, Clustering, Linear/Mixed-Integer Programming, Heuristics) Strong Python experience (scikit-learn, pandas, numpy, optimisation libraries) Experience building production-ready ML or optimisation solutions Solid understanding of CI/CD, Git version control, and cloud platforms (AWS preferred ...

imbalance exposure, generation patterns, demand profiles, and commercial optimisation. Required Skills and Experience Technical Skills Proficiency in Python and associated data science libraries (NumPy, Pandas, SciPy, scikit‐learn, PyTorch/TensorFlow). Strong experience with time‐series modelling (ARIMA, Prophet, LSTMs or similar). Understanding of optimisation methods (linear, mixed ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

Python skills by building a car price prediction app using Python and Streamlit. Step 6 – Python for Data Learn essential Python libraries like NumPy, Pandas, and Matplotlib for data manipulation and visualisation. Step 7 – AI Sentiment Analysis Project Work with Hugging Face to build a sentiment analysis classifier using real ...

applications, including memory management. Experience with widely used tools in data science and machine learning. Developers should be somewhat familiar with libraries like NumPy, pandas, scikit-learn, and PyTorch. Proficiency in testing approaches and frameworks like pytest as well as automation tools like Github Actions or Travis CI for maintaining ...

Software Engineer with up to 6+ years of hands-on Python experience. Familiarity with AWS Serverless and related technologies would be advantageous. Strengths in Pandas, Polars, Pytest, Postgres, and CI/CD is essential. If you're interested in Agile methodologies, and have a curiosity about DDD and Event-Driven ...

support decision-making. You will collaborate with cross-functional teams to identify trends, patterns, and insights from large, complex datasets. Requirements Fluent Python, Pandas, Numpy, Matplotlib & Scikit-Learn 5+ consecutive years living in the UK Bachelor's or above in a STEM field (e.g., Maths, Physics, Data Science, Statistics, Computer ...

environments Deep understanding of algorithm selection, model complexity trade-offs, and overfitting/underfitting dynamics Strong proficiency in Python and ML ecosystems (scikit-learn, pandas, NumPy) Experience with deep learning frameworks (PyTorch or TensorFlow) Practical knowledge of deep learning architectures (CNNs, RNNs, Transformers) and when to apply them Strong ...

processing times for large-scale financial datasets. Historical Depth: Processing per-minute data points spanning 24 years of market history. Vectorized Performance: Moving beyond Pandas—leveraging Polars for multi-threaded, Rust-backed data manipulation and Dask for distributed compute across clusters. Execution Engine: Native integration with SpiderRock for complex Equity ...

Practical Tool Exposure Gain experience with frameworks and technologies commonly used by UK employers. Key Tools & Technologies Python – Core programming for data analysis NumPy & Pandas – Data preparation and manipulation Matplotlib & Seaborn – Visualisation and exploratory analysis TensorFlow, SciPy, Scikit-learn – Machine learning fundamentals Spark – Scalable data processing Flask & Streamlit – Deploying APIs ...

Practical Tool Exposure Gain experience with frameworks and technologies commonly used by UK employers. Key Tools & Technologies Python – Core programming for data analysis NumPy & Pandas – Data preparation and manipulation Matplotlib & Seaborn – Visualisation and exploratory analysis TensorFlow, SciPy, Scikit-learn – Machine learning fundamentals Spark – Scalable data processing Flask & Streamlit – Deploying APIs ...

Practical Tool Exposure Gain experience with frameworks and technologies commonly used by UK employers. Key Tools & Technologies Python – Core programming for data analysis NumPy & Pandas – Data preparation and manipulation Matplotlib & Seaborn – Visualisation and exploratory analysis TensorFlow, SciPy, Scikit-learn – Machine learning fundamentals Spark – Scalable data processing Flask & Streamlit – Deploying APIs ...

analysis tools Experience working with real‐life timeseries data of physical systems Experience with data pre‐processing and cleaning Experience working with Numpy, Pandas, Polars and other standard python toolboxes for data analysis Independent and driven person who can work autonomously and take initiative, but also a team player ...

meaningful features, develop detection logic, and communicate findings effectively to non-technical stakeholders. Essential Skills & Experience Strong Python for data processing and analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability ...

meaningful features, develop detection logic, and communicate findings effectively to non-technical stakeholders. Essential Skills & Experience Strong Python for data processing and analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability ...

meaningful features, develop detection logic, and communicate findings effectively to non-technical stakeholders. Essential Skills & Experience Strong Python for data processing and analytics (e.g., pandas, numpy; scikit-learn or equivalent) Structured data expertise: joins, aggregations, data cleaning, handling missing data/outliers, basic data modelling concepts Feature engineering: ability ...

algorithms Some exposure to mathematical optimisation through university modules, projects, or internships Experience working with numerical or data libraries such as NumPy and pandas Basic understanding of optimisation concepts including constraints, objectives, and feasibility Nice to have Experience with optimisation frameworks such as Pyomo, OR Tools, Gurobi, or CPLEX Familiarity ...

algorithms Some exposure to mathematical optimisation through university modules, projects, or internships Experience working with numerical or data libraries such as NumPy and pandas Basic understanding of optimisation concepts including constraints, objectives, and feasibility Nice to have Experience with optimisation frameworks such as Pyomo, OR Tools, Gurobi, or CPLEX Familiarity ...

algorithms Some exposure to mathematical optimisation through university modules, projects, or internships Experience working with numerical or data libraries such as NumPy and pandas Basic understanding of optimisation concepts including constraints, objectives, and feasibility Nice to have Experience with optimisation frameworks such as Pyomo, OR Tools, Gurobi, or CPLEX Familiarity ...

machine learning methods; Eye for quality and attention to detail; Fluency in English (written and verbal communication) is required; Proficiency in Python (e.g. pandas, scikit-learn); Good command of one additional language (e.g. Chinese, French, Italian, German, Spanish...) is valued. MINDSET Interested in weather and natural perils modelling (wildfires, hail ...

context) Must-have Strong analytical & problem-solving skills: Able to decompose messy, real-world problems and craft tailored solutions. Proficient in Python & data science: pandas/Polars, NumPy, scikit-learn, Jupyter, Plotly (or similar) Confident with data cleaning, analysis, transformation, and visualisation. Excellent communication: Advanced written and spoken English; concise … Actions), SQL/Postgres. TypeScript fluency: Able to read TS and collaborate on data contracts with the Command team. Our environment Python, Polars/pandas, NumPy, scikit-learn, Plotly, SQL/Postgres, NVIDIA cuOpt, HERE APIs, AWS (S3, ECS/Lambda, SNS/SQS), Docker, GitHub Actions, TypeScript/Node ...