Vetted Looker Professionals

“Built and deployed a production generative AI chatbot at NVIDIA using LangChain + GPT-3 integrated with internal data sources, cutting response time nearly in half and improving CSAT by ~12 points. Also delivered LLM-driven QA tools by fine-tuning Hugging Face transformer models and deploying via an AWS-based pipeline (Lambda/Glue/S3) with orchestration (Airflow/Step Functions), CI/CD, Kubernetes, and monitoring (MLflow/Splunk/Power BI).”

Babita Aswani

Screened

Senior Customer Success Operations Manager specializing in B2B SaaS and AdTech

Fremont, CA9y exp

“Customer success / operations professional from PubMatic (ad tech) focused on onboarding and growing enterprise publisher accounts. Leverages analytics tooling (Looker/Tableau) and monetization KPIs (fill rate, eCPM) to drive adoption, retention, and expansion, including a reported ~30% usage lift over six months and cross-functional A/B-tested product changes that increased revenue.”

Sam McKenzie

Screened

Mid-level Business Operations & FP&A professional specializing in RevOps automation and GTM strategy

Remote7y exp

“At BuildZoom, led cross-functional alignment to launch a new product (Data Explorer) and grew it from $0 to $1.3M ARR in 12 months. Leverages analytics and BI tooling (HubSpot, Looker, Tableau, Sisense) to build executive dashboards and drive strategic decisions, including redesigning sales incentives to emphasize recurring revenue.”

Mayuresh Kanade

Screened

Director-level GTM and Customer Success leader specializing in Enterprise AI and SaaS

Redlands, CA18y exp

“Global sales and customer success leader with 20 years across the US, UK, and India who is now developing a buyer-first B2B platform focused on data sovereignty and shifting control from seller CRMs to enterprise buyers. Has worked with VC-backed startups and portfolio companies, including GTM efforts around AI/ML and cloud ecosystems such as Snowflake, Dataiku, Databricks, and Azure.”

“ML/AI engineer with Goldman Sachs experience building production fraud detection and RAG-based trading insights systems end-to-end. Stands out for combining real-time ML infrastructure, GenAI retrieval systems, and compliance-aware design, with measurable impact including nearly 25% false-positive reduction and improved analyst productivity.”

“Founder of an algorithmic trading startup who reports raising $25M+ over roughly the last three years. Has spent several years working closely with VC funds, focusing on fundraising and lead generation with VC/PE firms, and is strongly committed to entrepreneurship and scaling new technologies.”

“Candidate combines fraud analytics experience at Citi with a clinical AI capstone involving reproducible ML pipelines for imaging and notes data. They stand out for turning messy, high-volume data into decision-ready reporting, automating evaluation workflows, and translating analytics into operational impact—from fraud rule changes to retention metric adoption.”

Akshaya Rajagopalan

Screened

Mid-level Full-Stack Software Engineer specializing in cloud SaaS and accessible web apps

Waterloo, Canada6y exp

“Frontend engineer who leads end-to-end delivery of complex workflow-driven React + TypeScript products on top of Rails/GraphQL backends, with a strong emphasis on typed API contracts, scalable architecture, and automated quality gates. Shipped major features (e.g., inventory reservation at Jobber) using feature-flagged rollouts, close QA collaboration, and performance-focused iteration.”