Work

Changing the product when growth changed customer value.

I co-founded And1Analytics and led its evolution into Monster Roster. When identical lineups split customer winnings, I led the team to build a guided optimizer with algorithm-backed recommendations and user choice.

Original Monster Roster optimizer illustration: a mobile interface with three recommended player cards marked Locked.
Monster Roster · Original optimizer illustrationOpen full image (new tab)
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And1Analytics: $100K in early revenue

I co-founded And1Analytics in high school in 2015. We sold algorithm-backed daily-fantasy lineup recommendations through social media and a website, helping customers choose a roster without doing all the underlying research themselves.

From my high-school senior year through the end of my freshman year at Georgetown, And1Analytics generated $100K in cumulative company revenue. It was the original business that became Monster Roster.

A winning lineup exposed a scaling limit

One recommended lineup put multiple customers in a shared first-place finish in a large tournament. That success helped build demand.

As the business grew, I saw the limit in selling everyone the same completed lineup: customers entering the same contest could compete for the same winnings. I wanted to keep the guidance they valued while giving them a say in the roster.

Give customers choices around the recommendation

A fully unrestricted builder would give customers freedom but put more research back on them. I led a multidisciplinary team to build a guided optimizer combining algorithm-backed locks, recommendations and user choice. Locks held recommended players in the lineup; they were not guaranteed winners. Customers chose among model-selected options for the remaining positions, using player cards and a final roster view.

I owned product direction and experience design. Engineers and quantitative collaborators implemented the software and recommendation logic. Shared choices could still produce overlapping lineups.

Original Monster Roster player-selection interface showing a row of running-back choices, a selected player and supporting player information.
Original player-selection illustration. Customers chose the remaining players around a recommended core. Historical example content.Open full image (new tab)

Let customers track the picks they chose

Customers repeatedly used historical filters to check earlier recommendations. I designed a tracking feature that let them select recommendations to follow and review their results over time. It tracked their chosen picks, not transactions imported from sportsbook accounts.

Leading the team

I managed engineering, data science and design. I separated their working loops: mockups and beta feedback for customer experience, with distinct iteration and testing for engineering and data.

1,000+ paying customers across the venture

Across And1Analytics and Monster Roster, we acquired 1,000+ paying customers as the venture grew into subscription web and mobile products. It became the first company selected for the Philadelphia 76ers Innovation Lab.

After freshman year, I took three years away from Georgetown to pursue the business. I returned in 2019, and my founder role ended that December. I completed my BA in Psychology in 2022.

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