Role:
- As a Data Scientist, you will be working closely with data analysts, research analysts and portfolio managers to build the next generation of data visualization tools to support the firm's research and investment process.
- You will be working in an Agile environment with a highly dynamic and cross-functional team, overseeing the life cycle of our data.
Requirements:
- Proficiency in Python and experience with data analysis libraries such as Pandas and NumPy.
- Understanding of object-oriented programming and software architecture.
- Ability to write clean, maintainable, and efficient code.
- Basic understanding of React and web development.
- Strong analytical skills and great attention to detail.
- Self-starter with the ability to work independently in a multi-disciplinary environment.
Preferred:
- Prior experience with the FastAPI framework.
- Familiarity with Kubernetes and good CI/CD practices.
- Familiarity with SQL and database management systems.
- Knowledge of software testing, including unit and integration testing.
Additional Points:
- This role is data-centric and focuses on Python-based data engineering and backend development rather than frontend technologies like React (but is good to know), emphasizing efficient data processing, transformation, and API-driven workflows.
- Data wrangling and transformation using Pandas, NumPy, and Python-based ETL workflows.
- High-performance data ingestion, processing, and storage with optimized pipelines.
- Backend API development using Fast API, ensuring scalable and efficient data delivery.
- Containerized deployments and orchestration with Kubernetes, facilitating robust data services.
- Integration with structured and unstructured data sources, ensuring high data integrity and performance.
- Prioritize candidates with strong expertise in Python, Pandas, and backend data processing, rather than frontend development with React.
- Look for experience in data pipeline optimization, API design, and distributed data systems.
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