Sectors:
Locations:
Min Investment:
Max Investment:
Target Investment:
(2022 - 2023)
Venture Capital / Private Equity Apprenticeship
(2018 - 2018)
2018
2018
● Personally invested in companies representing verticals such as SaaS and digital healthcare. ● Identified and sourced investment opportunities within a healthcare-focused team, as well as across other verticals including consumer, enterprise, FinTech, and Telecomm. ● Contributed to developing efficiencies for the sourcing process and developed relationships with CEOs and founders at over 100 venture-backed startups and potential IPO / M&A candidates. ● Conducted initial and deeper due diligence of potential VU Venture Partners portfolio companies (factors involved in analysis include: market size, founder and product market fit, business model, competitive landscape, scalability and exit potential, understanding the cap table, etc.). ● Analyzed potential alternative deals including M&A, leveraged buyouts, and debt and equity financings; completed standalone operating models, valuations, and merger and LBO models. ● Drafted investment evaluations and recommendations. ● Represented VU Venture Partners by delivering a speech on the market potential of cross-border medical treatment at a “Reverse Demo Day” event in San Francisco. • Worked closely with and learned from top performing Managing Directors, including Andrew Zalasin (Former General Partner at RRE Ventures for ~20 years, a $1.5B venture fund), and J. Skyler Fernandes (Powerlist 100 VC, Founder of Simon Venture Group (corporate VC for Simon, S&P 100, leading retail fund) and Cleveland Avenue).
2020 - 2021
2020 - 2021
● Maintained a portfolio of recurring and new clients in California and the Atlantic Northeast. ● Served as Point-of-Contact for select high net worth clients to provide personalized communication of relevant banking-related information, as well as assist with pandemic relief lending and various other obligations such as outstanding debt with the bank. ● Also served as part of a specialized pandemic relief review team: - Processed high volume of loan applications for funding. - Supported team members and adjacent triage and processing teams with analyzing loan applications and government policy reports to determine the risk involved and expedite any potential funding obstructions. - Ensured all loan applications met SBA standards including amount of funding and forgiveness, liabilities, and payroll. - Communicated with clients to acquire missing or extra documentation to satisfy loan application confirmation for funding. - Utilized Salesforce and other database resources to enforce compliance policies including KYC.
2019 - 2020
2019 - 2020
● Role specialized in developing unique liquidity solutions for vested and otherwise illiquid clients, primarily, finance industry professionals. ● Served as part of a specialized pandemic relief review team: - Emergency relief loans required triage and processing of high volumes of loan applications within extremely constrained time periods. - Underwriting of loan funding calculations. - Risk assessments and calculations of loans required the construction and utilization of Excel Templates.
2016 - 2019
2016 - 2019
• Designed, implemented, and back tested trading algorithms using Quantopian’s iPython Library and Python NumPy for the creation of more complex statistical structures. • Primarily utilized medium frequency trading strategies including long-short positions (simultaneously long and short in the market). - Long-short positions required the construction of Python NumPy arrays of ranked assets in the market. - Automated strategy subsequently goes long the top n equities of the ranking, and short on the bottom n for equal amounts of capital. • Minimized portfolio risk by utilizing Python NumPy ranking models (momentum indicators / Score) to ensure rebalancing of equity market neutral positions (50% outperforming / 50% underperforming) which ensured zero net exposure to various market factors. • Minimized risk on certain long positions by utilizing call-options to delta hedge. • Also utilized low frequency trading strategies including currency carry trades. - Currency carry trades required the construction of Python lists of preferred high-yielding currency / low-yielding currency pairs. - High-yielding currency funded the trade with a low-yielding currency. • Medium frequency trading strategies produced consistent 10% returns (5% returns in more volatile markets). • Constrained horizon (typically 5 to 10 days) prioritized small wins which would accumulate to greater overall returns. • Stop loss was adjusted to 2% to 3% instead of the typical 7% to 8%. This adjustment ensured a 3-to-1 profit-to-loss ratio.
2014 - 2017
2014 - 2017
• Developed trading models for spot currency pairs based on breakout strategies (primarily Swing High and Swing Low). - Breakout Trading: genuine breakout is followed by a bold candle. The candle closes above the support resistance. - Swing High and Swing Low: breakout trading with a “V” shape form (swing high is defined by a strong rally, quickly followed by a strong selloff, and vice versa). • Developed trading strategies using market information, financial news, and charting analysis (Morningstar, CB Insights, Thomson One Banker, NetAdvantage S&P, etc.).