Elijah Johnson Email & Phone Number

New York, Ny, Us

New York, Ny, Us

Sunnyvale, California, United States

Predictive Insights: Conducted in-depth analysis of machine learning models to improve Google Cloud client operations, saving $1.5M annually through optimized predictive analytics.E-commerce Analytics: Analyzed and refined AI-powered recommendation systems for enterprise e-commerce clients, increasing conversion rates by 20% and boosting client revenue by $10M+.Automation Efficiency: Supported the development of data pipeline automation tools, reducing processing delays by 30% and improving operational efficiency for enterprise partners.Model Evaluation: Evaluated and fine-tuned machine learning algorithms, improving decision-making accuracy by 25% and safeguarding $5M in transactions annually.Cross-Team Collaboration: Partnered with engineers, data scientists, and product managers to deliver actionable insights, achieving a 95% client adoption rate for deployed AI solutions.

Delivered customized AI solutions for e-commerce brands, including Allbirds and Hims, boosting sales by 30% and saving over 500 hours annually in manual workflows.Example: Developed a dynamic pricing model for Allbirds’ online store, increasing revenue by $250K in Q4 2022.Partnered with startups like Notion AI and Carta to integrate AI-powered chatbots, driving a 15% lift in conversions and improving customer satisfaction scores.Example: Implemented a multilingual chatbot for Notion AI’s global expansion, reducing response times by 50% and improving NPS (Net Promoter Score) by 20%.Provided automation strategies for SaaS companies, including Canva and Zapier, increasing operational efficiency by 40% and reducing costs by $500K annually.Example: Automated subscription billing processes for Zapier, eliminating manual errors and saving 150+ hours/month.TechCrunch Disrupt Hackathon Winner: Created an AI-powered sales prediction tool.Google Cloud Hackathon Finalist: Designed a smart traffic optimization model.

San Francisco Bay Area

Fraud Detection Optimization: Collaborated with the machine learning team to evaluate and improve fraud detection models, reducing false positives by 30% and safeguarding $10M in annual transactions.Revenue Analytics: Designed dashboards and reports to track and analyze payment trends, uncovering insights that led to a 15% increase in revenue for small business clients.Data Pipeline Automation: Assisted in automating payment reconciliation processes, reducing manual intervention by 40% and saving over 200 hours per month for operational teams.Cross-Functional Collaboration: Partnered with product managers and engineers to implement data-driven solutions that enhanced user experiences for 500K+ SMB customers.Predictive Insights: Analyzed large-scale transactional data to identify customer behavior patterns, enabling proactive fraud prevention and improving decision-making accuracy by 25%.

Berkeley, California, United States

Collaborated on a machine learning research project focused on predictive analytics for retail optimization, resulting in a 15% improvement in inventory efficiency for participating partners.Designed and implemented neural network models to classify customer purchasing behaviors with 92% accuracy, leading to a conference presentation at NeurIPS 2022.Published internal research papers on scalable AI deployment strategies for startups in collaboration with faculty advisors.

Generate a lead pipeline for Brand Partnerships, Publisher Development, and Strategic Partnerships sales teamsCollaborate with Account Executives to ensure the successful hand-off of clientsMaintain clean record keeping of sales outreach and contacts in SalesForce