Senior Quant Developers

Job Description:

•             In terms of experience junior or mid (as long as they have the hard skills)

•             No prior knowledge of financial products or experience is required

•             They just have to be a self-starter, able to work well on their own with specific direction/guidance minimal hand-holding the most important thing is the tech skills

Data Scientist / Quant

Soft skills

·                  Curiosity and analytical mindset

·        Ability to learn new concepts and domains quickly

·        Versatility to work in a partial greenfield environment

·        Comfortable working with a broad scope with a geographically distributed team

·        Able to work independently on a wide range of data engineering and analytical tasks

Hard skills

·                  Very strong python with good code hygiene

·        Experience developing and testing data processes e.g. ETL, scraping, transformation etc.

·        Experience exploring and working with new datasets, assessing data quality and exploring for valuable insights - preferably with financial or time-series datasets

·        Familiarity with orchestration tools e.g. Apache Airflow

·        Good understanding of cloud solutions - we are AWS based.

·        Experience working with distributed compute frameworks to handle large data volumes e.g. Spark

·        Experience building visuals for expert and non-expert audiences - preferably using plotly/dash

·        Good source control practices and some experience with CI/CD

·        Comfortable building and deploying containerised solutions.

Nice to have

·                  Experience developing and deploying machine learning models

·        Experience working in financial markets

·                  Knowledge of best practices when back testing models.

Day to Day Duties

·                  Implement data on-boarding (ETL, web-scraping, etc.) and database management

• Implement best practices for data transformation, manipulation, and storage solutions 
• Build and maintain fundamental market models for supply and demand
• Build and maintain fundamental and price-based analytics (e.g. visualizations and dashboards)