Earn regular income by selling options, and manage your risk using Little John's proprietary ML models!Building an open-source package and ML- Saas company enabling traders to do their own research and successfully manage their portfolio.

The Sweater Cashmere Fund is the VC fund for everyone and the flagship fund for Sweater Ventures. The Sweater Cashmere Fund seeks to provide long-term capital appreciation through an actively managed portfolio of private, venture capital investmentsAsk me about our Portfolio Companies!

Using ML to protect IP from being stolen by foreign nations! (looking at you China)

Amira Invest is the marketplace that provides the structure and transparency needed to let everyday people trust the opinions investors share on the internet.Accomplishments as a Founder:- Built a team of 5 incredible engineers on minimal budget. Established a culture of remote-first excellence while working across 3 timezones- Architected an application with a serverless backend and a frontend deployed on Google Play and the App Store (details on the stack can be found here https://mobile.twitter.com/thehirschibar/status/1501990441645916171)- Designed our UI in Figma and translated the features into - > API specs - > jobs to be run - > cloud resources- Lead the team to produce 1200+ commits, 300+ PRs and hundreds of tickets in a monorepo with full CI/CD. The result: 30k+ lines of high caliber code. -Designed an ML recommendation engine delivering personalized content to each user's feed. - Built a following of hundreds across our waitlist and social media platforms. - Worked with investors to raise capital to build the above and to prepare for our upcoming fundraising round. Most importantly, I've learned tons of lessons along the way.

Develop and deploy python models and scripts to automate our vendor onboarding process, enabling us to scale our production output by 145x. Product utilized SpaCy library for NLP.Build microservices that integrate via RESTful APIs (python, flask, swagger, terraform, docker, AWS) to enable our customers to self-service and to schedule their requests for data extracts. Enabling our report output to increase instantly by 60% with the infrastructure to scale with our growing customer base.Built a proprietary dataset and performed data research (decision trees, regression) on company firmographics to predict likelihood of a data breach occurring within an organization based solely on the company's firmographics.Data wrangle on the daily in python using various cloud systems (Postgres, Athena, elasticsearch, mongoDB, dynamo DB, S3) to provide data and analysis for customers and internal management. Developed data driven strategic product ideas and supported them in front of management.You wear lots of hats at small company! Modeling, backend development, visualization, all part of the job!

Steer product strategy for the Dealer Auto Lending Business. I provide data driven insights to management to determine the most customer friendly and profitable opportunities for our business. Insights are produced utilizing SQL, Python, command-Line, and vba coding to make/manipulate models and cloud-based data. I help the company apply machine learning and human judgement to provide the optimal customer experience.

I provided coverage of the Industrials sector as one of eight senior analysts that managed a multi-million dollar fund on behalf of private investors and the university. The fund followed a strict value-investing mandate, actively pursuing equities that presented strong economic fundamentals, and cheap valuation multiples relative to their histories. Developed screening criteria based on strategy, moat, business fundamentals and historical stock performance to determine investment universe and watch list candidates out of the 620 publically traded industrial stocks (traded on US exchanges). Research presentations and investment theses were routinely prepared and presented to the investment team, determining whether stocks should be bought/sold or added to the watch list.SInce inception the fund has outperformed its benchmark 7 out of 10 years, by an average of 1.7% per year.

Developed and proposed a business case to change our current home loan credit policy, increasing the possible loan size credited to customers by 120%. Policy was expected to generate a 20% increase in loan profit within the business' NY footprint. Presented deck directly to MVP of Home LoansBuilt queries analyzing industry and internal data to provide inputs of our NPV model. Built custom VBA tools to enable the quick manipulation of 1000s of NPV model iterations to support my case. My recommendation was implemented shortly after the completion of my project

While working for Siemens full time, at night I conducted research, submitting two papers detailing the economic outlook for Germany and Switzerland to be published for use by the portfolio managers. The research was used in the creation and marketing of a new global portfolio. (the links below lead to posts citing my work, enabling effective due diligence for the portfolio)

Defended a sell recommendation to CFA Institute representatives in state research competition, predicting underperformance of a Utah utility stock. The stock price subsequently dropped 18% over the next month.One of five team members representing the University.