Josh Lemaitre

Lead AI/ML product and engineering for Brokerage Technology, architecting scalable analytics platforms and deploying semantic LLM-based solutions to drive enterprise decision-making and operational excellence. Delivered an agentic AI for generation and execution of Snowflake SQL through a conversational interface. Developed LLM-powered metadata generation pipeline for enterprise search platform, enabling semantic search capabilities and improving content discoverability across the organization.

Vice President – AI/ML Engineering at Fidelity Investments (2024-08 – Present)

• Lead AI/ML product and engineering for Brokerage Technology, architecting scalable analytics platforms and deploying semantic LLM-based solutions to drive enterprise decision-making and operational excellence.
• Delivered an agentic AI for generation and execution of Snowflake SQL through a conversational interface.
• Developed LLM-powered metadata generation pipeline for enterprise search platform, enabling semantic search capabilities and improving content discoverability across the organization.
• Led vendor evaluation and POC development for customer journey analytics, creating data-driven insights from unstructured sources to inform strategic initiatives.
• Prototyped investment syndicate business proposal for Fidelity Labs incubation, enabling retail investors to access institutional investment opportunities through collaborative pooling structures.

Vice President – Product Management, Fidelity Labs at Fidelity Investments (2023-01 – 2024-08)

• Drove innovation strategy at Fidelity Labs, leading AI product development from concept to deployment. Collaborated cross-functionally to align emerging technology initiatives with business objectives and regulatory requirements.
• Developed LLM-powered financial concierge prototype delivering personalized guidance, demonstrating transformative potential for customer engagement despite regulatory constraints.
• Built and deployed AI-powered PII redaction tool, automating compliance with data privacy regulations and enabling secure cross-team data collaboration.
• Prototyped internal API marketplace accelerating AI service discovery and integration, reducing time-to-market for enterprise AI solutions.

Manager, Data Science at Thomson Reuters (2016-06 – 2022-12)

• North America regional data science lead, developing AI applications for business transformation.
• Established global knowledge-sharing programs and technical curriculum supporting AI literacy, adoption and best practices; 600+ active members, > 10,000 employees directly engaged with program content.
• Architected ML-powered entity resolution system for CLEAR platform using Bayesian inference and NLP, reducing false positives by 20% and false negatives by 34%. Championed AWS migration, overcoming institutional cloud resistance.
• Developed deep learning model for contract clause deviation detection and white-collar crime risk assessment, enabling proactive compliance monitoring. Inventor for US Patent 11,681,735.

Senior Data Scientist at Thomson Reuters (2014-07 – 2016-06)

• Founding member of Thomson Reuters Labs, exploring AI applications across product portfolio. Developed proof-of-concept solutions demonstrating business value of emerging ML technologies.
• Evaluated multiple third-party data sources for alpha-generation in support of the Starmine quant product suite.
• Built IP litigation prediction model (AUC 0.85) providing portfolio valuation framework and actionable risk insights for legal professionals.
• Developed NLP pipeline for standardized extraction of non-GAAP tax metrics from XBRL-formatted SEC filings.
• Created Bayesian inference model for banking client predicting business outcomes based on loan syndicate participation history.
• Promoted to lead Boston/Toronto data science team.

Director of Analytics at RichRelevance (2009-07 – 2014-07)

• Global leader of product analytics, insights, and data science teams spanning teams in North America, EU, and EMEA, driving innovation and actionable insights through research, business intelligence and analytics infrastructure.
• Deployed reinforcement learning recommendation system using multi-armed bandit algorithms, typically achieving 10% CTR improvement and 5% conversion lift, measured directly by AB tests.
• Created universal product taxonomy using Word2Vec embeddings, enabling consistent categorization and improved recommendation relevance across 400+ retail clients and consumer goods advertisers.
• Developed and standardized analytics libraries and experiences in support of self-service on-demand reporting dashboards for sales and account executives.
• Established quarterly business review standards and operating metrics in support of retail and CPG customer engagements (Procter & Gamble, Unilever) and sales cycles.

Technical Program Manager at RichRelevance (2008-06 – 2009-07)

• Employee #10 managing agile engineering teams delivering enterprise personalization products and analytics for major retailers (Walmart, Sears, Target).
• Architected product analytics and reporting for internal and external customers.
• Scrum mastered four major product releases, including recommendation engines and client-facing performance dashboards.
• Built BI dashboards supporting strategic decision-making and customer launches with A/B testing analytics.
• Represented company as subject matter expert at ecommerce conferences on data science and retail personalization.

Operations Researcher at Overstock.com (2006-09 – 2007-07)

• Founded operations research group, developing quantitative models for inventory planning, sales forecasting, and strategic pricing. Collaborated with buyers and marketing to align model outputs with business constraints.
• Increased holiday profit margins 15% by implementing price change procedures and managing buyer adherence.
• Liquidated $73M excess inventory with $20M revenue salvage versus traditional clearance, using optimized discounting strategies.

Director, Website & Email Marketing at Overstock.com (2005-06 – 2006-09)

• Directed diverse R&D team – researchers, analysts, operators, marketers – in program management of experimentation, segmentation, and personalization strategy for 30M monthly visitors and 10M email subscribers.
• Executed 100+ experiments driving $20M revenue growth and significant conversion improvements.
• Established experimentation best practices framework and corporate branding style guide.

Marketing Manager at Overstock.com (2004-11 – 2005-06)

• Managed $500K affiliate marketing budget across third-party email campaigns.
• Delivered 100% YoY revenue growth in comparison shopping engine channel.
• Created marketing efficiency model evaluating cost, revenue, acquisition, and LTV to optimize budget allocation.

Master of Engineering in Operations Research – Massachusetts Institute of Technology (2008)

Bachelor of Science in Economics – Duke University (2001)