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Technical leader combining deep ML/AI expertise with hands-on engineering and strategic thinking, currently serving 4M+ users with cutting-edge GenAI features and personalized experiences. From developing patented innovations in automotive and defense industries to architecting enterprise AI solutions, I've consistently pushed technical boundaries through successful transitions across diverse domains. Uniquely positioned at the intersection of AI innovation and engineering excellence, I combine PhD-level expertise in interdisciplinary scientific research with enterprise ML architecture experience.I excel at bridging domains: from hardware prototyping to MLOps modernization, research labs to production systems, and individual contribution to team leadership. This versatility enables me to tackle complex challenges from multiple angles - whether optimizing CI/CD pipelines for 200% faster builds or architecting ML systems with FastAPI and Prefect. Throughout my career, I've mentored diverse technical talent - from undergraduate interns to data science masters student capstone projects and postdoctoral fellows at Insight Data Science - helping them bridge the gap between academic excellence and industry impact. Passionate about identifying technological opportunities early and building scalable solutions while fostering the next generation of technical leaders.
Weightwatchers
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Staff Data ScientistWeightwatchers Sep 2024 - PresentNew York, Ny, Us• Leading development of large-scale generative AI features serving 4M+ members, including automated recipe import and food image recognition capabilities, while optimizing for peak winter diet season performance and scalability.• Driving significant CI/CD improvements through Python monorepo optimization, implementing service decoupling and incremental builds with uv that achieved 200% faster build times.
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Senior Manager, Ai And Data ScienceWeightwatchers Mar 2024 - Sep 2024New York, Ny, Us• Led WeightWatchers' generative AI strategy, managing both internal cross-functional engineering teams and Google-preferred vendor partnerships to prototype recipe chatbots and menu scanning features.• Made critical strategic pivot based on pilot study results, redirecting team focus from chatbot development to traditional value-adding tool feature in the app after identifying gaps in member AI readiness.• Successfully championed long-planned initiative to optimize growth funnels, directing implementation of contextual bandits for cancel-save offers that preserved $7M in customer lifetime value (LTV)
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Manager, Machine Learning Engineering & Data ScienceWeightwatchers Dec 2021 - Mar 2024New York, Ny, Us• Led development of Experience Engine, implementing ML models for predicting member disengagement risk and content affinity, while collaborating with product teams to integrate personalized content delivery infrastructure across the WeightWatchers platform• Successfully advocated for data science needs in company-wide Universal Analytics Service (UAS) modernization, ensuring new unified schema supported advanced ML model training requirements while collaborating across Android, iOS, and web platform teams• Modernized MLOps infrastructure by leading migration to Prefect from in-house workflow orchestration, establishing scalable experimentation platforms while maintaining production stability• Doubled data science team size to 12 members while fostering culture of ownership through structured onboarding, mentorship programs, and delegation of infrastructure responsibilities• Mentored two Columbia University masters student teams (8 students total) in developing generative AI prototypes for WW, teaching industry practices from version control to kubernetes deployment, resulting in successful demos of voice-based food tracking and AI recipe image generation at company-wide meeting
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Senior Data ScientistWeightwatchers Mar 2020 - Dec 2021New York, Ny, Us• Led development of an XGBoost-based ML model predicting key transitions in members' weight loss journeys, revolutionizing WeightWatchers' onboarding strategy and launching a multiyear initiative through cross-functional collaboration with product, design, and behavioral science teams• Championed early adoption of FastAPI to replace Flask across microservices, recognizing its integrated approach to API development with built-in Pydantic validation would eliminate dependency conflicts and reduce boilerplate compared to Flask's fragmented ecosystem of third-party packages• Architected separation of Business Logic and ML layers in service infrastructure, significantly improving A/B testing capabilities and reducing cross-team dependencies for model deployment• Developed and deployed an XGBoost classification model powering intelligent Invite-A-Friend content targeting, successfully pitching to stakeholders and shepherding from concept to production• Fostered cohesion across 12-person technical team during transition to remote-first environment, championing virtual collaboration practices and maintaining team culture through structured mentorship, pair programming, and regular social connections
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Data ScientistWeightwatchers Jan 2019 - Mar 2020New York, Ny, Us• Architected and deployed a scalable Recipe Recommendation Engine using Flask, implementing production-grade API frameworks by integrating tooling for request validation, authentication, and response marshalling to enable team-wide microservice development• Developed a synthetic user behavior simulation system to enable QA testing of ML-powered features, generating realistic historical user data to validate personalized vs. non-personalized experiences in testing environments• Built an NLP pipeline using spaCy that parsed and structured complex food descriptions into dependency graphs, enabling the development of intuitive food-builder features that simplified tracking of customizable items like coffee and meals
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Technical AdvisorInsight Data Science Sep 2019 - 2022San Francisco, Ca, Us• Mentor PhD graduates and post-docs as they build prototypes of ML-powered data products over the course of a fast-paced 4 week program.• Provide both technical and product advice as they prepare to present their MVPs to hiring data teams across the industry.• Conduct technical mock interviews and guide fellows in navigating the interview process from preliminary screens through accepting an offer. -
Data Science FellowInsight Data Science Sep 2018 - Dec 2018San Francisco, Ca, Us• Built a mountain bike trail recommendation system “Rec & Ride” using a hybrid approach of content and collaborative recommender systems.• Scraped 3,000 trail pages for trail metadata and 1.5 million ridelogs for user-item interactions from Trailforks.com and engineered features using techniques including tf-idf text vectorization and SVD matrix factorization.• Deployed a web app on AWS EC2 built with Dash and Flask to deliver personalized ridingrecommendations to users based on their favorite trails and riding history.
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Phd Research AssistantUniversity Of Delaware Aug 2013 - Sep 2018Newark, De, UsInvestigated cartilage mechanics, specifically fluid transport within cartilage and how it relates to cartilage lubrication. My experiments combined the mechanical testing of cartilage explants with novel biomedical imaging techniques using laser scanning confocal microscopy. My research suggests that being active is critical to the transport of nutrients into cartilage and to keeping it hydrated to maintain its remarkably low friction.Collected and analyzed many types of data. I have developed algorithms in Matlab and Python to segment a variety of images, including 3D micro-CT images and multichannel 2D time series images from confocal microscopy, and to detect events in time series data from sensor signals. I have also used Matlab, Python, and R to perform statistical analyses and visualizations of this data for numerous presentations and publications.Designed and fabricated custom experimental test devices. I selected the actuators, sensors, power sources, and signal conditioners used in these devices, wired the electrical system, machined many of the metal components, and wrote significant portions of the control code in LabView. These devices had unique spatial constraints as they often had to interface with existing commercial imaging systems, which made this a difficult engineering challenge. -
Product Development InternStryker Jun 2013 - Aug 2013Kalamazoo, Mi, UsDesigned surgical tools for use with computer-aided knee replacement surgery and evaluated functional prototypes in a cadaver lab setting with a team of surgeons and engineers. Surveyed consulting surgeons and summarized their procedural preferences to form the guidelines for a standardized surgical workflow to aid in the design of new instrumentation. -
Product Development InternStryker Jun 2012 - Aug 2012Kalamazoo, Mi, UsCombined surgeon and engineering inputs to design instruments for use in computer-aided knee replacement surgery. Rapidly iterated through prototypes using Pro/Engineer and additive manufacturing to quickly incorporate surgeon feedback and revise designs accordingly.
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R&D InternHutchinson Industries - Defense & Mobility Jan 2012 - May 2012Responsible for the creation of tire shielding concepts through all stages of the development process -- from the whiteboard, to CAD model, to fabrication of the initial prototypes. Created the dual tire shield (DTS), which protects the sidewalls of tires on trailers pulled by military convoy vehicles from being punctured by bullets or debris in hostile and rugged environments. A patent for the DTS was granted in 2014.
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Innovations InternSaint-Gobain Performance Plastics Jun 2011 - Aug 2011Solon, Oh, UsDesigned a new geometry and assembly method for self-lubricating composite polymer/sheet metal bearings that are used in the automotive industry. The unique design, along with accompanying tooling, rivet, and pin, allows for the bearings to self-assemble during the riveting process, significantly reducing manufacturing time and costs by eliminating steps in the typical assembly process. The patent application for this invention received Notice of Allowance at the end of 2017.
Brian Graham Skills
Brian Graham Education Details
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University Of DelawareMechanical Engineering -
The College Of New JerseyMechanical Engineering
Frequently Asked Questions about Brian Graham
What company does Brian Graham work for?
Brian Graham works for Weightwatchers
What is Brian Graham's role at the current company?
Brian Graham's current role is Staff Data Scientist at WeightWatchers |Technical Leader in AI/ML | Engineering Innovator | Bridging Research and Enterprise Solutions.
What is Brian Graham's email address?
Brian Graham's email address is gr****@****cnj.edu
What is Brian Graham's direct phone number?
Brian Graham's direct phone number is +197349*****
What schools did Brian Graham attend?
Brian Graham attended University Of Delaware, The College Of New Jersey.
What skills is Brian Graham known for?
Brian Graham has skills like Data Analysis, Matlab, Image Segmentation, Machining, Confocal Microscopy, Image Analysis, Micro Ct, 3d Printing, Microscopy, Biomedical Engineering, Image Processing, Microsoft Office.
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