j
jeel_gondaliya

Jeel G

@jeel_gondaliya

AI Consultant

Canadá
Inglês
Algumas informações são exibidas no idioma inglês.
Sobre mim
I am an experienced AI Consultant and Senior Machine Learning Engineer with a proven track record of building scalable AI-driven solutions across financial services and marketing. I specialize in designing LLM-based systems, predictive underwriting models, and personalized recommendation engines that drive significant revenue and efficiency. I am proficient in Python, PyTorch, and cloud infrastructure, with a focus on translating complex business problems into high-impact technical strategies.... Saiba mais

Habilidades

j
jeel_gondaliya
Jeel G
offline • 

Conheça meus serviços

Consultoria de Tecnologia de IA
I will build custom ai solutions to automate your business
A partir deUS$ 30 /projetoMais detalhes

Experiência profissional

Slalom

AI Consultant

Slalom • Período integral

Apr 2026 - Present • 6 mos

Lead AI and machine learning consulting engagements across financial services and marketing, translating complex business problems into scalable AI-driven solutions. Designed and evaluated LLM-based solutions, assessing build-vs-buy trade-offs, model capabilities, infrastructure requirements, and ROI to guide high-impact client decisions.

Homebase

Senior Machine Learning Engineer

Homebase • Período integral

Mar 2025 - Oct 2025 • 7 mos

Built an LLM-powered automated hiring system that staffed 50,000+ small businesses during a major product launch. Built and standardized experimentation workflows (A/B tests and holdout groups) to validate model interventions and measure downstream retention impact. Mentored junior data scientists to improve team velocity by 25%.

RBC_Capital Markets

Senior Machine Learning Engineer

RBC Capital Markets • Período integral

Mar 2022 - Mar 2025 • 3 yrs

● Designed and deployed personalized GIC recommendation engine serving 10M+ customers, increasing product engagement by 15% and generating $8M incremental revenue in the first year ● Led experiments using causal inference and uplift modeling to measure the impact of recommendation changes on user engagement and funnel conversion ● Led technical direction for balance forecasting system redesign, improving accuracy by 10% through hyperparameter optimization, feature engineering, and real-time prediction pipelines processing 500K+ transactions daily ● Pioneered LLM applications for internal knowledge management, building RAG-based systems that automated white paper generation and Q&A functionality, reducing research time by 40% for business analysts