Jan 2022 – Jan 2024 · 2 yrs · Atlanta, Georgia, United States

• Following a successful 4-year tenure leading data & ML teams at Meta, I took a strategic sabbatical to complete my graduate studies (started while at Meta) and deepen my technical expertise in modern ML systems. This intentional investment allowed me to transition from my prior self-taught foundations to formal mastery of emerging GenAI architectures, including LLMs, reinforcement learning, and transformers, positioning me at the forefront of the current AI paradigm shift.
• Strengthened technical depth through dual Master's degrees: implemented research on transformer architectures, built distributed ML systems, and applied emerging techniques in RL & NLP
• Led 4+ engineer teams on production ML projects: built market prediction system (-31% error), redesigned enterprise data pipelines (3x throughput), and deployed reinforcement learning models for dynamic pricing optimization

Jan 2018 – Jan 2022 · 4 yrs · New York City Metropolitan Area

• Responsible for data products, infrastructure, and ML systems supporting Meta Business product operations (~400 FTE). Cultivated a highly collaborative environment with cross-functional teams, partners, and senior leadership groups. Secured funding for and managed team with 12 funded positions across North America.
• Developed an ML-driven Product Quality strategy with the Senior Director of Operations, identifying a 12% issue prevention opportunity projected to generate incremental $1B in revenue across Meta's global support operations
• Led cross-functional ML data quality initiative improving model precision from 65% to 89% for high-value support categories, reducing ticket escalations 17% and saving $155M annually through optimized routing algorithms
• Built high-performing organization from 1 to 12 members to support expanded ML initiatives, securing funding for 3 net-new positions based on demonstrated team ROI and business impact
• Transformed team capabilities expanding ML project portfolio while developing 2 senior team leads, achieving 89% retention and 10 promotions despite 4 major organizational changes
• Implemented SDLC and Agile practices as Scrum Master improving ~20 person team’s velocity by 21%
• Designed and led scenario-based analyses, empowering stakeholder leadership to secure +50 FTE and +$115M in OPEX for Contingency and Long Range Planning
• Developed measurement & optimize strategy for client org’s service agents. Drove 43% of record +11% for stakeholder’s top priority KPI, Resolution.

Jan 2017 – Jan 2018 · 1 yr · New York City Metropolitan Area

• Owned measurement, attribution, and go-to-market campaign performance, embedding ML models into engineering practices to align predictive capabilities with product growth objectives. Led cross-functional team of 5 (3 data scientists, 2 analytics engineers) across multiple global geographies supporting new advertising product growth through optimization.
• Led global team (3 DS, 2 AE) to deliver ML-driven insights for new ad platform, driving 39% YoY growth and $110M in incremental revenue through effective measurement strategies aligned with Product and Engineering objectives
• Automated workflows with ML-powered solutions and data engineering, boosting release velocity by 27% and building culture of engineering excellence
• Embedded ML models into workflows to optimize forecasting accuracy, directly improving product performance and predictive capabilities

Jan 2015 – Jan 2017 · 2 yrs · New York, New York

• Led comprehensive ML, data science, and analytics functions at company level. Managed team of 5 (3 data scientists, 2 data engineers) with direct and dotted-line responsibilities across all data initiatives supporting student lifecycle and business optimization.
• Led ML team (3 DS & 2 DE) to reduce operational costs by $190K annually while improving student outcomes 28% through predictive modeling and process optimization
• Deployed ML for LTV/CAC optimization, boosting prediction accuracy 35% while cutting acquisition costs $190K annually through advanced customer modeling
• Authored requirements for new data infrastructure modernization, partnering with Data Engineering on implementation to support scalable data products

Jan 2014 – Jan 2015 · 1 yr · New York, New York

• As a Director of Data Science at Tapestry, I led a team of 3 analysts & 1 manager and was responsible for the analytics function for the Global Digital org at Coach, including insight generation as well as selection, and integration of advanced analytics tooling.
• Led reporting infrastructure build, resulting in +48% increase analysis throughput via automation.
• Partnered with Product and UX teams on roadmap on site and feature development.
• Led strategic sourcing and onboarding of vendors, accelerating the pace and enhancing the quality of insight generation, user experience research, and product development initiatives.

Jan 2012 – Jan 2014 · 2 yrs · New York, New York

• As the Analytics Manager at One Kings Lane, I oversaw a team of two analysts and drove insights for for product, marketing, creative operations, and retail. My role encompassed data-driven decision through ML-augmented ad-hoc analysis, A/B testing and descriptive analytics.
• Led discovery of revenue cannibalization through A/B test to measure customer behavior, recommending strategic adjustments to C-team which recuperated $15MM potential revenue (annualized).
• Engineered a predictive algorithm for Click-Through Rate on lifestyle imagery, enhancing photo selection strategy and boosting top of funnel micro-conversion rates by 16%.
• Created and rolled out comprehensive reporting and performance metrics for the Product/Mobile division, leading to web funnel optimization and a 9% improvement in conversion rates.

Jan 2008 – Jan 2012 · 4 yrs

• As a Data Science Consultant in the gaming industry, I founded and scaled a side-business into a gaming data consultancy. I leveraged data engineering to compile a comprehensive player database for trend analysis to increase my clients' profitability. My approach involved empirically validating data-driven strategies, which I also used to market my consultancy services.
• Data mined / segmented user information for trend analysis, developed solutions for 20+ global clients, create +125% growth in overall client profitability
• Optimized client workload via competitive analysis, resulting in 17% reduction of hourly workload
• Utilized modeling, Bayesian inference, metric construction, and back-testing in solution selling approach, growing initial investment of $600 to over six figures

Jan 2007 – Jan 2008 · 1 yr

• As a Senior Analyst at Johnson & Johnson, I supervised an analyst intern and played a key role within the team that handled service negotiations for the Consumer Products Division. I led projects focused on price optimization via vendor data modeling, managed global Request for Proposals, contract negotiations, and drove process improvement projects as a Six Sigma Green Belt.
• Actively managed $84MM of Finance, Marketing, Advertising services creating $3.8MM annualized savings
• Lead global graphics project, creating $1.4MM process related savings via price modeling
• Co-developed agency commodity strategy focusing on agreement consolidation, pay-for-performance modeling, reconciliation process
• Modeled group pricing strategies for negotiations, developed best-in-class Consumer model for renegotiations

Jan 2005 – Jan 2007 · 2 yrs

Jan 2005 – Jan 2005 · 0 mo

Jan 2003 – Jan 2003 · 0 mo · Pittsburgh, PA

• As an Intern on the Data Cleansing team, I specialized in refining vendor data for optimal use in Freemarkets' core reverse auction product. My expertise in Microsoft VBA and RegEx was pivotal in ensuring data accuracy and usability, significantly contributing to the development of a new Data Cleansing service.