Python/Apache/Spark doing Quant development in a Capital Markets Enterprise. These candidates will be building quantitative models exploring and working with new datasets, assessing data quality and exploring for valuable insights - preferably with financial or time-series datasets. There is also a Data visualization part as well as containerization and CI/CD **** THIS IS NOT JUST A PYTHON DEVELOPER POSITON, CANDIDATES MUST HAVE CAPITAL MARKETS/QUANT EXPERIENCE.
Required Location: Hybrid/Midtown New York City or Austin, TX 3 days a week.
Candidates must be LOCAL to the NEW YORK or NEW JERSEY or Austin, TX area and COMMUTE into the office THREE TIMES A WEEK . NO RELOCATION CONSIDERED .
1. How many years working with: Quant development
2. How many years working with: Python/Apache/Spark
3. How many years working with: CI/CD
4. How many years working with: AWS
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
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