15 of 15 Polars Jobs in the UK

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 architectures ...

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 architectures ...

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 ...

trading signals, translating research ideas into robust, production-ready codeDesigning and automating large-scale data pipelines for financial datasets using tools such as Polars, Pyarrow, Pandas and NumPyWorking closely with researchers, traders, and DevOps teams to integrate models into live trading environmentsContributing to architectural decisions and the long-term technical ...

/data models (forecasting, pricing, optimisation or similar) Strong Python proficiency and modern data stack exposure (SQL, Pandas/NumPy + PySpark; Dask/Polars/DuckDB a bonus) build, schedule and optimise Spark/PySpark pipelines in Databricks (Jobs/workflows, performance tuning, production delivery) Hands-on experience with ...

operating modern data pipelines with real ownership Have worked on research-, trading-, or decision-critical systems Are curious about modern data tooling (e.g. Polars, Julia, Rust, Lakehouse patterns ), even if you haven’t used all of it yet Prefer hands-on technical ownership Ideal Background Systematic funds, quantitative asset managers ...

rules engines, and data quality checks, with an emphasis on writing maintainable, well-structured code Experience using Python libraries for data wrangling (e.g. Pandas, Polars), modelling (e.g. scikit-learn), and visualisation (e.g. matplotlib) Experience with modern data tooling (e.g. Spark, Azure Data Factory) or the ability to implement equivalent capabilities ...

experimentation and validation Experience in the following is a plus: Modern data architectures (e.g. lakehouse or columnar analytics) High-performance data tools (e.g. Polars, Julia) System-design thinking and data-lifecycle awareness Performance-critical workflows or systems-level tooling (e.g. Rust) Relevant Backgrounds (Finance or Non-Finance) We consider candidates ...

tuning Python scripting for automation, parsing, rules engines, anddata-quality checks; ability to write maintainable code Experience with Python packages such as Pandas/Polars, scikit-learn, matplotlib Experience with modern data tooling (e.g., Spark, cloud data-integration tooling) or the ability to implement equivalent functionality in code Proven experience ...

technical and non-technical stakeholders, including coaches, scouts, analysts, and traders. Skills & Attributes Strong background in Python, with experience in data manipulation (Pandas/Polars) and statistical modelling. Industry experience in a data science role focussing on sports analytics or personal projects related to football data. Knowledge of advanced football ...

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 Options execution … Experience: 5–8 years in a Quant Dev or Systematic Trading environment at a top fund or bank. Coding Mastery: Expert proficiency in Python (Polars/Dask/FastAPI) and/or C++. AI Native: Proven ability to use LLMs and Machine Learning to solve complex financial time-series problems. ...

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 Options execution … Experience: 5–8 years in a Quant Dev or Systematic Trading environment at a top fund or bank. Coding Mastery: Expert proficiency in Python (Polars/Dask/FastAPI) and/or C++ . AI Native: Proven ability to use LLMs and Machine Learning to solve complex financial time-series ...

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, direct … GitHub 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/ ...

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, direct … GitHub 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/ ...

Data Engineer who enjoys building production-grade pipelines , optimising performance, and working with modern Python tooling (DuckDB/Polars) on time-series datasets I’m supporting a UK-based fintech in their search for a hands-on Python Data Engineer to help build and improve the data infrastructure powering … production) 📈 Ingest and normalise high-velocity time-series datasets from multiple external sources ⚙️ Work heavily in Python with a modern stack including DuckDB and Polars (plus Parquet/PyArrow ) 🧩 Orchestrate workflows and improve reliability (they use Temporal — similar orchestration experience is fine) ✅ Improve data integrity and visibility: validations, automated checks ...