12 of 12 Remote Permanent Polars Jobs

strong understanding of computer systems and how they operate. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualization and API libraries (matplotlib, plotly, streamlit, Flask, etc). Experience developing and implementing quantitative More ❯

3+ years of experience developing and deploying production-grade Python software. 3+ years of experience with Python and high-performance data libraries such as Polars and Pandas. Proficiency with JavaScript, SQL, and KQL. Experience with Extract, Transform, Load (ETL), Data Streaming, and Reconciliation. Experience building and maintaining deployment pipelines, including More ❯

of branching strategies, merge mechanisms, and repository management Demonstrated ability to build and maintain test automation frameworks and CI/CD pipelines Experience with Polars Veeva's headquarters is located in the San Francisco Bay Area with offices in more than 15 countries around the world. As an equal opportunity More ❯

Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or Pandas for high-performance data processing. Proficiency with cloud platforms (AWS, GCP, or Azure), including containerization and orchestration using Docker and Kubernetes. More ❯

a quantitative discipline (such as STEM subject or Economics). Proficiency in Python, with a solid understanding of Python libraries (such as NumPy, pandas, Polars, and scikit-learn) for data manipulation and statistical modeling. A minimum of 5 years experience working with Futures order book market data, with strong familiarity More ❯

restrictions Experience in programming languages and data structures such as SAS, Python, R, SQL is key. With Python background, particularly familiarity with pandas/polars/pyspark, pytest; understanding of OOP principles; git version control; knowledge of the following frameworks a plus: pydantic, pandera, sphinx Additionally, experience in any or More ❯

restrictions Experience in programming languages and data structures such as SAS, Python, R, SQL is key. With Python background, particularly familiarity with pandas/polars/pyspark, pytest; understanding of OOP principles; git version control; knowledge of the following frameworks a plus: pydantic, pandera, sphinx Additionally, experience in any or More ❯

working within a cloud environment. Experience with big data technologies (e.g. Spark, Databricks, Delta Lake, BigQuery). Experience with alternative data technologies (e.g. duckdb, polars, daft). Familiarity with eventing technologies (Event Hubs, Kafka etc ). Deep understanding of file formats and their behaviour such as parquet, delta and iceberg. More ❯

tools like AWS SageMaker and Lambda, and you'll know your way around Git, SQL, and common Python data science libraries (like pandas/polars, scikit-learn, xgboost/lightGBM, and TensorFlow/PyTorch). Bonus points if you've worked with linear programming, or have experience in time series More ❯

forecasting Back-testing and refining models Collaborating with the trading team Working in a fast-moving environment Utilizing a modern data science stack, including Polars, DuckDB, and dbt Requirements: Strong mathematical foundation, ideally in probability, statistics, or machine learning Expertise in data-driven model development Creativity in model design Ability More ❯

forecasting Back-testing and refining models Collaborating with the trading team Working in a fast-moving environment Utilizing a modern data science stack, including Polars, DuckDB, and dbt Requirements: Strong mathematical foundation, ideally in probability, statistics, or machine learning Expertise in data-driven model development Creativity in model design Ability More ❯

you. What Youll Do Design, build, and maintain Python services that power critical financial workflows. Work with modern data processing tools like pandas and polars to transform and analyze large datasets. Build async Python services using asyncio , and develop event-driven systems integrating AWS services (Lambda, SQS, EventBridge, ECS, etc. … impact Opportunities to shape the technical direction and engineering culture as we grow Our Tech Stack Languages: Python (3.10+), SQL Frameworks/Libraries: pandas, polars, dataclasses, asyncio, pytest Data: PostgreSQL, AWS S3 Infrastructure: AWS (Lambda, ECS, SQS, EventBridge), Docker, Terraform CI/CD: GitHub Actions, pre-commit, mypy, flake8/ More ❯