Sophie Searcy

Data Science education company whose main product is a 12 week bootcamp that covers the breadth of the field of Data Science. Current role (>2 years) is primarily EM & PM.

Product: Oversees the design and development of all new products. Leads cross-functional product teams of >15 individuals. Current product portfolio represents 25% of 2021 revenue and accounts for 100% of growth opportunities.
Management: Directly manages team 6 Data Scientists. Introduced industry best practices including company-wide Eng and DS prioritization flow, code reviews, and continuous integration. Oversaw increase in internal collaboration: YOY 7x commits and 20x issues/pull requests. Managed codebase, resolving disputes between ICs.
Instruction: Taught and mentored 100s of students entering data science. Authored dozens of lessons including: SVMs, Data Science Ethics, Deep Learning, Generative Adversarial Networks.

Wearables start-up building fabrics that pair electrical stimulation to apps. Fundraising: \$20k convertible note (\$1.5M cap, 20% discount). Competitions: The Bridge (Coca Cola’s Accelerator) finalist (ranked 22/200). AlphaLab Gear National Hardware Cup semi-finalist. Vogt Awards finalist (\$25k non-dilutive funding). XlerateHealth finalist. Bucks for Bright Ideas winner.

Proof of concept: Designed and built hardware and software proof of concept. Validated underlying technology, collected data on 100+ customer experiences in target audience and demonstrated product-market fit.
Scalable design: Led engineering teams managing user data and designing a product for 10k/yr volume: the entirely in-house product stack included electronics hardware, firmware, and desktop app.
Human resources: Managed HR. Designed collaborative, version controlled, company Handbook.

Project manager: Managed a data science team developing FOSS tools for replicable cross-platform video data processing at “Big Data” scale.
Web experiments: Designed full-stack web apps for large (n~1,000) behavioral experiments and administered experiments through Amazon Mechanical Turk. Mentored data scientists in full-stack design.
Interdisciplinary research: Lead author of interdisciplinary work on the foundations of learning and computational tractability of learning algorithms. Presented work in journals and conferences.