Remote (Eastern Time Zone)
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Data Science Manager, Style Discovery
San Francisco, CA
Style Discovery team is responsible for assessing, attributing, and recommending all new merchandise across Stitch Fix.
Design the Line refactor: rebuild team’s primary capability. Has enabled: reduced maintenance burden, faster iteration cycles, cross-functional access to previously siloed tech stack.
Merch Attribute Extraction: automated attributed of new items that enables access to high-impact capabilities downstream, and greatly expands the potential impact of all merchandise teams.
Recruited and retained a highly engaged and productive team.
Executive Director of DS, Principal Data Scientist
New York, NY
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: Oversaw the design and development new and growth products across org. Led 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.
Instruction: Taught and mentored 100s of students entering data science. Authored dozens of lessons including: SVMs, Data Science Ethics, Deep Learning, Generative Adversarial Networks.
New York, NY
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.
Research Assistant, PhD Candidate
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.
Searcy (2019) AI is Broken
Searcy and Blinder (2018) Making Faces: Conditional generation of faces using GANs via Keras+Tensorflow
Searcy, W.K. Vong, Lane & Shafto (In prep) Cause and affect: Subjectively rational causal inference about affective content.
Searcy (In prep) Levels of expressivity: Learning across incompatible representational levels
Searcy & Shafto (2016) Cooperative Inference: Features, objects, and collections. Psychological Review.
Searcy & Shafto (2014) Learning biases for teaching boolean concepts.
(2010) Energy Efficiency Comparisons of Wireless Communication Technology Options for Smart Grid Enabled Devices
PhD (ABD), MS
University of Louisville | Experimental Psychology: Computational Cognitive Science
MEng, BS Eng
University of Louisville | Electrical and Computer Engineering
University Fellowship Award (2 years Full tuition plus stipend), National Merit Scholarship (5 years full tuition plus stipend)