Biography

A freshly minted doctor of business administration who is a data scientist with a passion for all things involving machine learning and artificial intelligence. Especially, as these cutting-edge technologies are used to develop and launch highly complex, mission-critical applications that enhance market visibility, improve trading strategies, develop alpha and mitigate risks across global investment management, banking, and financial services organizations.

Education

Sacred Heart University

Doctor of Business Administration in Finance
December 2021

Sacred Heart University

M.S. Computer Science & Information Technology
August 2016

University of Connecticut

Bachelor of Science in Mathematics
May 2014

Core Competencies

    Machine Learning, Artificial Intelligence
    Financial Modeling & Forecasting
    Hands-on experience Python
    Market Data / ETL
    Equities, Equity Options
    Project Supervision
    Problem Solving
    PowerPoint Presentations

Technical Proficiencies

  • Languages:
    • Python 3.x | HTML | Matlab
  • Libraries/Packages:
    • Pandas, Numpy, SciPy, Scikit-Learn, Matplotlib, PyKalman, Flask, Dash, Plotly
  • Asset Class Domains:
    • Equities, ETFs, Equity Options
  • Modelling Tools:
    • Matlab R2019a-R2021a, EViews 9.5
  • Development Tools/IDEs:
    • Visual Studio Code, Workbench CE 6.0, Microsoft Management Studio
  • Operating System Platforms:
    • Windows Server 2012R2, Windows 10/11
  • Databases:
    • SQL Server 2014/16, MySQL
  • Market Data Sources:
    • PR News Wire, Interactive Brokers, Bloomberg API and Active Tick
  • Source Control/Project Management:
    • Git, Jira
  • Applications:
    • MS Excel, MS Word, MS PowerPoint, Beyond Compare, Notepad++, Agile software development

Professional Experience

Karya Capital Management L.P., New York, NY

Quantitative Researcher
Aug 2020 – Jul 2022

Assisted in backtesting of equity option trading strategies. Performed data extraction & loading into MySql relational database. Cleaned and performed anomaly detection. Made schema modifications to database as requirements changed. Worked on management presentations describing backtest results.
  • Wrote Python ETL applications to load data into MySql database.
  • Implemented Kalman Filter algorithm to analyze regime shift states of the 10-year Tsy Yield and S&P 500.
  • Developed a dashboard using the Flask web development framework along with Dash and Plotly to provide an interactive data visualization in real time.
  • Investigated the weakening inverse correlation of the VIX and S&P 500..
  • Applied a Logit model to predict the likelihood of corporate bankruptcy for small, medium and large firms as measured by market capitalization using data from the Center for Research in Securities and Prices/ Compustat Merged Database.
  • Wrote ETL applications to import financial historical data using flat files into MySql database..

Awards & Honors

  • Upsilon Pi Epsilon
  • International Honor Society for Computing & Information