Jennifer Evans
Sr Product Manager, Ai, Llm, & Machine Learning @SmartAsset
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WORK HISTORY
Sr Product Manager, Ai, Llm, & Machine Learning @SmartAsset
Portland, ME, US
Driving the SmartAsset Voice AI product strategy • Built 2-year AI & LLM Roadmap for Voice AI, LLM and machine learning technology to fully automate human calls, audit call recordings for compliance and drive new data products to market for SmartAsset (SA)\'s customer base.• Built Voice AI workflows to dial calls for Financial Advisor lead generation resulting in a higher success rate than average of human call centers leveraging Bland.ai Voice AI Agent platform.• Designed Call Recording Audit workflow to transcribe 100% of lead generation calls (Voice AI and human) and evaluate on 85+ criteria for compliance and revenue recognition. This was infeasible prior to LLM technology implementation.• Implemented LLM automation for call analysis & disposition with 98.2% accuracy compared to manual auditing.
EDUCATION
Indiana University - Kelley School of Business
MBA, Business Administration and Management, General
Georgia Institute of Technology
Master of Science (MS), Computer Science
San José State University
BS, Computer Science
SKILLS
ABOUT JENNIFER EVANS
Technical product leader with 14+ years of experience designing AI/ML solutions, driving $800MM+ in business impact. My background combines deep technical expertise in machine learning (MSCS ML, Georgia Tech) with a proven ability to architect scalable AI solutions at Amazon, Cisco, Nile, and SmartAsset. I thrive in high-growth, startup environments where automation drives customer value. I am passionate about leveraging AI/ML to create measurable business outcomes while ensuring responsible deployment.Highlights:* Revenue and Growth Impact: Architected and implemented ML solutions driving $800MM sales increase through improved Amazon search relevance.* Security Product Development: Drove $28.3MM first-year sales through successful implementation of Cisco’s IoT security solution incorporating ML for anomaly detection in industrial environments. Reduced IoT on-prem deployment cycles from 2 weeks to 2 days through DevOps automation.* Automation & Internal Platform Leadership: At Nile, directly engaged with customers to identify process and product gaps, then architected system integration, platform, and deployment automations enabling 10x customer growth while maintaining service quality across fragmented systems.* Workflow AI Automation Excellence: Built LLM-powered call recording audit automation evaluating 100% of Voice AI and human-dialed lead-generation calls across 85+ criteria, replacing incomplete manual processes.
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