Vetted Dashboard Development Professionals

“COO of Greenopia (pre-seed, pre-revenue) who has built the company’s operational foundation over the past 18 months—supporting fundraising, SEC/crowdfunding setup, and coordinating app and self-serve business onboarding/assessment systems. Brings a metrics-driven operating approach (OKRs, balancing metrics/unit economics) and has advised other startups (e.g., sports betting) to refocus effort on the highest-value customer segments.”

“Built and deployed a production LLM conversational AI system at OpenAI supporting chat, summarization, and semantic search at 1M+ requests/day, driving major latency (40%) and accuracy (25%) improvements through Pinecone optimization and tighter RAG with re-ranking. Also has Amazon experience improving recommendation systems by translating ML metrics into business terms to boost CTR and conversions, with strong MLOps/orchestration depth (Airflow, MLflow, SageMaker, Kubeflow).”

“Growth marketing and marketing ops leader who joined a PE-owned SaaS business after $150M in annual sales and built the demand gen function from the ground up (roles, processes, tech stack, and reporting). Implemented SiriusDecisions-based lead processes, Salesforce-driven lead scoring/routing, and multi-touch attribution, then enabled sales via Challenger training—driving $231M in pipeline and improving marketing ROI to $6 pipeline per $1 spent.”

“Senior Program Manager / HR Chief of Staff (Global Industrial) specializing in cross-functional risk remediation, HR systems implementations, and M&A compliance. Delivered measurable outcomes including closing 18 payroll audit findings in 16 weeks, rolling out SAP SuccessFactors performance management to 2,000+ employees with major adoption gains, and remediating 600 I-9s in 6 weeks to avoid ~$3M in exposure; experienced operating with high confidentiality across large-scale M&A.”

“NVIDIA engineer who built and shipped a production LLM-powered enterprise knowledge system (summarization, transcription, and Q&A) that cut document retrieval time ~30%. Deep hands-on experience with RAG (FAISS/Pinecone), GPU-accelerated microservices on AWS, and reliability/safety practices (Guardrails AI, prompt A/B testing, canary releases) plus strong MLOps orchestration across Airflow, Step Functions, and Kubernetes GitOps.”