About
New York City native living as a digital nomad in Europe!
My educational and work background is in engineering and computer science. I have previously served in technical development roles in the Ins... urance, Artificial Intelligence, and Quantitative Finance industries.
I am most familiar with Python, Java and SQL and am excited to adapt to roles utilizing other technologies. I am very detail-oriented and have soft-skills ingrained in me from my time spent working in collaborative team environments.
Graduated from Columbia University School of Engineering and Applied Sciences in 2017 (SEAS '17)
"Stephen has been a great asset to us at [English Language School]. He leads weekly speaking clubs and produces very engaging and original language learning content. I highly recommend him for the role of private tutor."
-Anastasia A.read more
Experience
Engineering Intern on Data Provisioning Squad
Allianz Quantitative Analytics
Jun 2022 - Nov 2022
- Tested that optimizations made to Allianz SMART TripleB Java library resulted in correct data outp... ut
- Wrote Jupyter notebooks to automate partitioning of Oracle SQL database tablesread more
Customer Experience/API Integrations Engineer
Pypestream
Jul 2018 - May 2019
- Created, maintained, and documented library containing over two dozen genericized Python “action n... ode” scripts which encapsulate and automate the implementation of API integration details. Scripts are selected from the library and linked together by solution designers during AI design to control flow of execution within chatbot sessions.
- Single handedly made major contributions to key CX initiatives such as the development of “action node” debugging tools, streamlining of code review procedures, and production of highly reusable logic within “action node” code
- Weekly reporting prepared for team leads not familiar with computer programmingread more
Software Engineer
Systematic Trading Firm
May 2017 - Jan 2018
- Produced and wrote whitepaper for first implementation of complex pricing model with Python Panda... s and q/kdb+, resulting in 80% faster calculations parameterized to handle 3rd party futures data for 14 markets.
- Used Python, Pandas and q/kdb+ to design 8 daily data comparison email reports highlighting and quantifying discrepancies exceeding 1/10th basis point to retire legacy data production environment.
- Automated parsing and addition of monthly return spreadsheet reports to SQL database using Python, Pandas and SQLAlchemy, optimizing data consolidation process by 3X while saving company over $1000 / year.read more