Python Analytics Developer

Title: Analytics Developer, Hybrid 3~4 days in-office 8am 4pm CST workday.
Nashville on-site( People who will relocate to TN will work)
Hybrid 3~4 days in-office 8am 4pm CST workday.
Job Role: Create and refine quant algorithm scripts in Python to solve complex financial problems.
Close to a Data Science Engineer type of role.
Investment Product
- Tax Advantaged Taxable Bond SMAs (differentiate our Taxable SMAs with an industry first systematic tax optimization for taxable bonds)
- Capacity to develop additional Taxable SMA products (potentially offshore solutions, completion fund products, non-USD, etc)
Type of Quant/Algo/Analytic Software to Develop - Automated Transition Analysis (real-time transition from existing bonds to Client portfolios via Service Center)
- Automated Proposals (cash funded proposals/model portfolios via Service Center)
- Trade Rationales (unparalleled transparency for advisors into SMA trading activity and benefits)
- Transition Scorecards (proactive touch point summarizing onboarding process and portfolio changes/benefits )
Technical Skills:

• Strong knowledge o f Python programming language and its frameworks, with a focus on back-end development.
• Knowledge of software development principles and Object-Oriented development and design patterns ( C# experience a plus)
• Experience with back-end technologies such as Oracle, SQL Server, .NET, REST API, microservices , etc.
• Understanding of parallel programming concepts and packages parallelization/multiprocessing/cloud .
• Working experience/knowledge of Azure is a plus (CI/CD, Kubernetes, Data Factory, Containers/Pods/Docker, [ AWS is ok - Azure equivalent ]

Quantitative and Analytical Skills:

• Strong mathematical and statistical skills, with the ability to apply them to develop financial algorithms.
• Experience in developing and optimizing quantitative algorithms for financial applications.
• Strong analytical and problem-solving abilities, with a focus on developing innovative solutions to complex problems.
• Ability to troubleshoot and optimize existing analytics solutions for improved performance.