Vetted Data Analysis Professionals

“Candidate comes from SaaS and healthcare analytics rather than game development, but has strong end-to-end ownership experience building real-time, high-availability systems in Python/AWS. They highlight measurable impact across performance, throughput, uptime, and cost reduction, including queue optimization and predictive ICU utilization pipelines, and are looking to transfer that systems engineering foundation into Unity/gameplay work.”

“Software engineering candidate who built a compiler-like Python tool to translate between Python code and UML-style diagrams (and back). Also has hands-on AWS experience building a distributed pub/sub system using services like Lambda, API Gateway, ELB, WAF, VPC, and DynamoDB, plus ML projects using Kaggle datasets (e.g., diabetes risk analysis).”

“Supply chain/sourcing professional focused on semiconductor tooling NPI ramp-ups, owning vendor selection through production and delivery. Demonstrates strong cost and trade-risk mitigation (e.g., avoided 25% Section 301 tariff via HTS/landed-cost analysis) and measurable supplier performance turnarounds (OTD improved to 95%) using SAP MRP, shortage analysis, and structured supplier governance.”

“Backend engineer who built a serverless AWS Lambda microservices backend for a parenting assistance mobile app, including a personalized recommendation system optimized to sub-500ms via precomputed scoring and DynamoDB caching. Demonstrates strong production pragmatism: CloudWatch-driven performance tuning (provisioned concurrency), zero-downtime phased schema migrations, and robustness patterns like optimistic locking and request deduplication. Also led a refactor of an LLM RAG pipeline to improve retrieval quality and cut latency from ~5s to ~3s.”

“Cloud-focused engineer experienced deploying and stabilizing complex production systems that span APIs, infrastructure, and automated workflows, with a strong observability and safe-release mindset (feature flags/canaries/rollbacks). Has hands-on, customer-facing incident leadership, including executing DR regional failover during an AWS us-east-1 outage to maintain service and reportedly save a client ~$10M.”

“Org/people advisor with 20+ years applying systems thinking and data-driven methods to high-stakes change—spanning DEI transformations at an international consulting firm, profitability turnarounds in eldercare via company-wide facilitation, and executive coaching. Also designs compensation benchmarks for novel roles at international tech companies, enabling successful global hiring and growth.”

“ML/NLP engineer currently working in NYC on a system that connects complex unstructured data sources to deliver personalized insights, using embeddings + vector DB retrieval and a RAG architecture (LangChain, Pinecone/OpenSearch). Strong focus on production constraints—especially low-latency retrieval—using FAISS/ANN, PCA, index partitioning, and Redis caching, plus PEFT fine-tuning (LoRA/QLoRA) and KPI/SLA-driven promotion to production.”

“ML/NLP practitioner with experience building an embedding-based ad matching and search system at Vericast (BERT embeddings + similarity search) to replace a third-party taxonomy approach, evaluated via a human-curated gold standard. Also built a custom NER pipeline at Allstate for auto accident claims calls using a bidirectional LSTM and achieved 90%+ F1, with a strong emphasis on production-grade ML workflows (testing, CI/CD, orchestration, versioning, validation).”

Anvith Reddy Dodda

Screened

Mid-level AI Engineer specializing in GenAI, NLP, and MLOps

Remote, USA3y exp

“LLM/agentic-systems engineer with PayPal experience hardening an LLM-powered fraud support assistant from prototype to production, focusing on low-latency distributed architecture, rigorous evaluation/testing, and security/compliance. Comfortable in customer-facing and GTM contexts—runs technical demos/workshops, builds tailored pilots, and aligns sales/CS with engineering to close deals and drive adoption.”

Jincheng Pang

Screened

Principal Data Scientist specializing in healthcare analytics and medical imaging AI

Sudbury, MA11y exp

“Developed an LLM-driven recommendation agent in Azure Databricks to triage oncology patients and trigger second-opinion case creation using medical claims and EHR data. Uses ICD-10/CPT/J-code features in prompts, embeddings + vector DB similarity, and a backtesting framework emphasizing recall to avoid missing clinically relevant cases while supporting business revenue.”

“Finance data and reporting professional with PwC experience who bridges accounting and technology, especially around GL-related reconciliations, reporting accuracy, and close support. While not a direct PeopleSoft GL owner, they bring strong SQL-driven troubleshooting, ETL/data mapping remediation, and process automation experience that helped shorten close cycles and improve audit readiness.”

“Compensation professional with hands-on experience supporting complex year-end salary, bonus, and equity payment processes from the comp side of payroll. Built an Excel-based modeling tool to implement a new target bonus structure for a Technology population, and shows strong strength in reconciling incentive budgets, handling late-cycle pay exceptions, and putting approval controls around high-risk compensation scenarios.”

“Candidate has hands-on experience delivering production data and AI systems, including an AWS-based real-time data platform for a financial client at Deloitte and a production RAG workflow that cut manual search time by 40%. They stand out for combining strong data engineering depth with practical LLM governance, incident debugging, and stakeholder management across business and risk/compliance teams.”

“Analytics professional with Deloitte experience building SQL and Python workflows for revenue, pipeline, and opportunity analytics at scale. They combine strong data engineering and modeling skills with business-facing delivery, citing impacts including 8-10% conversion improvement, ~$700K revenue protected, 12% YoY project acquisition growth, and 15% retention improvement in financial services.”

“Python backend engineer with experience combining traditional API/microservices development and GenAI integrations, including healthcare claims workflows. Particularly compelling for teams building production AI systems: they pair hands-on work with LLMs, RAG, LangChain-style orchestration, and AWS deployment with a strong emphasis on reliability, security, and engineering discipline.”

Briant Trainer

Screened

Principal cloud consultant specializing in ERP, public sector, and enterprise implementations

California, USA25y exp

“Senior cloud/functional consultant with deep experience implementing Oracle and Infor solutions for large public-sector clients, especially permitting, licensing, and EAM-related workflows. Stands out for owning full lifecycle delivery, translating highly regulated requirements into complex configured workflows, and running large-scale UAT/test management across multi-module enterprise programs.”

“Early-career candidate with startup and nonprofit go-to-market experience spanning retailer matching, vendor acquisition, and external outreach. At a B2B SaaS startup, they evaluated 2000+ retailers by rebuilding fit criteria for each client, and at ASCENDtials they built a vendor outreach system from scratch that produced a 30+ vendor portfolio.”

Betsie Hoyt

Screened

Director-level Product Management leader specializing in SaaS, AI, APIs, and mobile products

18y exp

“Senior product leader in construction technology with experience at Trimble, where they helped reshape a fragmented 15-acquisition portfolio into a platform strategy that became central to how a $250M business is sold and supported. They combine enterprise platform thinking, AI product delivery, and change management, including launching a voice-based LLM workflow for regulated field reporting and coaching cross-functional teams into stronger product practices.”

“Operator-founder currently building two apps to MVP, handling everything from market research and test-user feedback to hands-on product changes in FlutterFlow and Visily. In a prior large-scale portfolio environment, they brought order to a highly disorganized 100+ person, 26-value-stream delivery organization by standardizing Jira workflows, creating stakeholder cadences, and lifting predictability from 30% to 86%.”

“AI Product Manager who also operates as a product marketer/CRM lifecycle lead, focused on behavior-driven onboarding and retention. Has delivered measurable growth through segmentation, multi-channel lifecycle programs, and experimentation (e.g., activation +23%, TTFV -30%, retention +14%), and led a cross-functional chatbot integration that improved course completion (+23%) while reducing refunds (-15%).”

“Built and productionized an autonomous research agent (AutoGPT) in a Docker/Kubernetes environment with Pinecone-based long-term memory and custom Python tools for analysis, visualization, and report drafting. Implemented layered guardrails (prompt templates, automated validation, self-critique loops, and monitoring) and achieved ~25% reduction in manual report generation time while scaling the workflow to support multiple concurrent users.”

“Talent Acquisition Operations leader who has managed teams up to 10 and owns end-to-end TA ops areas (strategy, selection, employer branding, and process/tech optimization). Recently standardized fragmented hiring by moving to a one-funnel approach with competency weighting and recruiter triage, already improving time-to-fill. Led Gem implementation/integration and uses ATS analytics (SmartRecruiters) plus post-hire performance data to validate sourcing and selection quality.”

“Operations/process-focused leader with hands-on manufacturing and quality mindset: improved product stability by preventing oxidation via inert gas and oxygen monitoring, and implemented sensor-based automation to maintain conditions without manual intervention. Uses time studies and benchmarking to redesign workflows (reported ~60% labor reduction per batch) and trains teams on GMP/regulatory and contamination-control practices using practical demonstrations.”

Hardik Goyal

Screened

Senior Integration Developer specializing in enterprise automation and data integration

United States4y exp

“Frontend-focused engineer with experience building and optimizing React-based dashboards and reusable component libraries in a multi-team, internal open-source-style environment at Merck (ClearSight Forecasting Dashboard). Also handled production user issues on a live streaming platform (GameSee.tv) and built a financial application from scratch at Manipal Business Solutions, owning backend services, middle-tier APIs, and third-party integrations.”