Vetted Collaboration Professionals

“HRBP/Employee Relations professional with Accenture and Clyde & Co experience, combining strong people analytics with risk-focused change management. Notably coded and analyzed four years of exit interview data to drive targeted retention and compensation actions across offices, and partnered with North America HR/Finance leadership on shared-services transition planning involving protected-class risk analysis.”

“AI/ML engineer who has deployed production LLM/transformer-based systems for merchant intelligence and fraud/support optimization, delivering +27% merchant engagement and +18% payment success. Deep experience in privacy-preserving, PCI DSS-compliant data/ML pipelines (Airflow, AWS Glue, Spark, Delta Lake) and scalable microservices on Kubernetes, plus proven cross-functional delivery in healthcare claims analytics at UnitedHealth Group (12% HEDIS claim reduction).”

“Operations/people-ops leader focused on early-stage, growth, and turnaround environments, with hands-on experience implementing UKG (HRIS) and Lever (ATS) to scale without adding headcount. At Niagen Bioscience, drove a 25% improvement in time-to-fill and cut administrative workload by 30% in 6 months, led a company-wide optimization initiative to reduce silos, and coached a VP of Finance into a successful CFO transition that included restructuring the finance org and upgrading key talent.”

“Engineering/technology leader from Ticketmaster who drove a domain-driven modernization strategy for legacy commerce platforms while launching new revenue features (add-on sales like merch/parking/hotels). Rebuilt and scaled teams post-COVID by reorganizing around business domains and implementing federated architecture governance, including a distributed-saga-based order orchestration approach that improved resilience and enabled partial-order success.”

“Backend/data engineer with production experience building credit/fraud enrichment services and checkout pipelines on AWS (EKS + Lambda) using FastAPI, Kafka, Postgres, and Redis, with a strong focus on reliability patterns (timeouts/retries/circuit breakers) and observability. Has also built AWS Glue/PySpark ETL into S3/Redshift with schema evolution and data quality controls, and modernized legacy credit decisioning into Java/Node microservices with parallel-run parity validation and feature-flag rollouts.”

“Built and deployed a production AI/ML SRE copilot that uses RAG over real-time Splunk signals plus deployment/runbook data to generate grounded incident summaries and next steps, cutting time-to-contact by 30%. Treats the knowledge corpus like a production dataset (quality gates, semantic chunking, metadata enrichment) and runs golden-dataset automated evals to ensure reliability, while partnering closely with ops/support leaders through discovery sessions and metric-driven demos.”