Responsibilities
- Develop and implement applications that achieve measurable market impact
- Build and optimize real-time and batch pricing algorithms
- Collaborate within a multidisciplinary team of engineers and data scientists
- Engage in deployment to Kubernetes environments and integration with existing data systems
- Ensure efficient data processing leveraging Python libraries (Polars/Pandas, numpy, sklearn)
- Work with SQL to design, query, and manage databases
- Produce and consume events from Kafka for data streaming
- Other duties as assigned
Qualifications & Skills
- Minimum 4 years of experience in Machine Learning or Data Engineering roles
- BSc/MSc in a Scientific or Quantitative field
- Strong proficiency in Data/Machine Learning, Python, and SQL
- Experience with Linux environments, including Bash scripting and basic network tools (SSH, SCP, FTP)
- Extensive experience DS stack: Python {Polars/Pandas}, numpy, sklearn
- Familiarity deploying to Kubernetes and working in cloud environments
- Kafka producer experience
- Collaborative mindset, business-focused attitude, and ability to meet tight deadlines
- Ability to read and edit others' code, ensuring quality and clarity
Nice to have:
- Experience working across multiple asset classes
- Knowledge of asset classes such as ETFs, Fixed Income, Equities, or FX is preferred
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