Vetted Power BI Professionals

“Early-career analytics candidate with hands-on experience in SQL/Python data pipelines, Tableau reporting, and marketing engagement analytics across internship and startup settings. Stands out for combining rigorous data quality practices with practical AI system design, including an end-to-end GPT-4 grading capstone that emphasized explainability and human oversight.”

“ML/AI practitioner with hands-on experience shipping production time-series forecasting and RAG-based customer insights platforms in an enterprise setting. At BASF, he improved seed sales forecasting beyond naive baselines using model selection tailored by brand size, and he also led a RAG solution over Salesforce reports, complaints, and surveys that reached 2,000+ users with strong daily engagement.”

“Candidate is pursuing a CTO role and has helped multiple startups turn early technology concepts into concrete, real-world technical requirements. They cite a systems science and mathematics background, along with experience at JPMorgan Chase, and appear strongest in technical strategy, concept fleshing, and identifying strong people to help teams succeed.”

“AI/LLM engineer with strong healthcare domain depth who has shipped production-grade agents for care coordination and clinical workflow automation. Stands out for combining Knowledge Graph RAG, LangGraph orchestration, and rigorous eval/guardrail systems to improve reliability in high-stakes environments, with measurable gains in review time, hallucination reduction, latency, and clinician adoption.”

“ML/AI engineer with hands-on ownership of a production LLM/RAG system at Goldman Sachs, focused on workflow automation and large-scale document search for operational teams. They combine strong MLOps and backend engineering skills with practical GenAI evaluation and safety practices, and cite measurable impact including 22% better task guidance accuracy and sub-second search across millions of records.”

Benjamin Feldman

Screened

Director-level application development leader specializing in FinTech and digital transformation

Boston, MA16y exp

“Hands-on engineering leader in a private-company/startup-like environment who builds full-stack financial systems and leads small teams. Notably replaced a failed third-party banking platform with an in-house Azure-based product integrating major bank APIs, driving $200K-$300K in annual savings and major workflow automation and performance gains.”

Claudia Perez

Screened

Director-level Chief of Staff and strategy operations leader in multinational environments

New York, NY26y exp

“Cross-functional strategy and operations leader with experience spanning telecom, nonprofits, logistics, consulting, and startup environments. Particularly strong in turning high-level strategy into executable operating models—most notably mapping 300+ cross-functional initiatives after a planning effort, work that became the basis for a PMO. Brings a rare blend of change management, operational rigor, and political savvy in complex organizations.”

“Sourcing/procurement professional with end-to-end ownership of vendor selection, negotiation, and delivery for AI-enabled workflow automation products. Uses structured scorecards, SLA/KPI-driven supplier management, and dual-sourcing strategies to reduce risk—delivering measurable outcomes like 18% cost savings, OTD improvement from 82% to 96%, and 25% rework reduction while navigating data quality drift and trade/duty exposure.”

“Talent & Recruiting Operations leader currently running high-volume, multi-state hiring at Brink’s, managing a team of 4 recruiters delivering ~1,600 hires/year. Known for operational redesign and analytics-driven workflow standardization that reduced time-to-fill to 32 days, plus leading Paradox AI rollout to automate screening/scheduling and improve speed and consistency across markets.”

“Software engineer with strong end-to-end ownership of search and listing systems (React/TypeScript frontend with Node.js + Spring Boot backends), focused on shipping fast while managing risk via feature flags, testing, and metrics. Demonstrated measurable UX/performance wins (reduced latency and search abandonment) and built internal observability tooling (dashboard + alerts) that improved incident response. Experienced with microservices reliability patterns including idempotency and dead-letter queues.”

“Built a production AI-driven QA automation platform using a multi-agent architecture (MCPs + LangGraph) to run parallel website tests across multiple device environments via automated image building and containerization. Currently collaborating with restaurant operators and managers to deliver an agentic restaurant analytics system, emphasizing deep domain discovery with non-technical stakeholders.”

“Backend/automation engineer who led the design of an OOP Python test automation framework for AWS infrastructure (Behave + Jenkins), cutting regression effort from weeks to a 3–4 hour run. Has hands-on cloud and DevOps experience across AWS (boto3, ECS, AMI automation via GitHub Actions) plus data/migration work including on-prem-to-cloud Oracle Retail DB migration with rollback planning and a Kafka + ML fraud-detection streaming pipeline.”

“Full-stack engineer with strong DevOps/AWS production experience who builds and operates multi-agent AI systems end-to-end (Streamlit/Python through Docker/Kubernetes and ECS/Fargate). Has delivered measurable outcomes: sub-2s latency and ~92% routing accuracy for an AI wellness assistant, shipped an AI-for-BI prototype in under 6 weeks cutting analysis time ~40%, and improved pipeline iteration speed ~35% via modularization and CI/regression checks.”

“CTO who ties technology strategy directly to business outcomes, building multi-year roadmaps with measurable ROI. Led major modernization (cloud, data platform, unified API, microservices + CI/CD) delivering 5x faster releases/deployments, 99.8% uptime, and 40% user growth without headcount increases, while scaling engineering from 15 to 80+ in ~18 months.”

“Data engineer at Capital One building AWS-based real-time and batch pipelines and backend data services for financial/fraud use cases. Has owned end-to-end pipelines processing millions of records/day, implemented dbt/Great Expectations quality gates, and tuned Redshift/Snowflake workloads (cutting query latency ~22–25% and reducing pipeline failures ~30–40%) while supporting 15+ downstream consumers.”

“Healthcare data engineer with hands-on ownership of claims/member data pipelines on a cloud analytics platform, spanning batch and streaming ingestion (Airflow/Kafka/Spark/Databricks) through serving for reporting. Emphasizes reliability and data quality via embedded validation, schema-drift detection, deduplication, and operational monitoring/incident response, plus pragmatic CI/CD and observability setup in early-stage/ambiguous projects.”

“Data engineer/backend developer who owned end-to-end pipelines and external data collection systems, including API ingestion and large-scale web scraping. Worked at ~50M records/month scale, improving processing speed by 20% and reducing reporting errors by 15%, and shipped a Rust-based internal data API with versioning, caching, and strong validation/observability practices.”

Sandeep Athota

Screened

Mid-level AI/ML Engineer specializing in cloud MLOps and production ML systems

Texas, USA4y exp

“AI/ML engineer at J.P. Morgan Chase who deployed a production financial-risk prediction platform combining CNN/LSTM/gradient boosting on AWS SageMaker, with automated drift-triggered retraining and governance-grade fairness testing. Leveraged SageMaker Clarify plus SMOTE and LLM-generated synthetic data to improve minority-group F1 by 0.12, and communicated results to non-technical risk/ops teams via Power BI dashboards.”

Pavan Kumar Malasani

Screened

Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and GenAI

Remote, USA4y exp

“GenAI/ML engineer in Citigroup’s finance environment who has deployed production RAG systems for investment banking under strict privacy and model-risk constraints. Built an internal-VPC Llama2 + Pinecone + LangChain solution with NER redaction and citation-based verification to prevent hallucinations, delivering major time savings, and also partnered with global finance executives to ship an AI early-warning indicator for treasury/liquidity risk.”

Yukti Kamthan

Screened

Senior Software Engineer specializing in AI/ML and data systems

Mumbai, India10y exp

“Built and shipped production LLM/AI agent systems including an NL-to-SQL query agent with semantic search and Redis-based caching, using schema-aware prompting and threshold validation to reduce hallucinations. Has orchestration experience running ML microservices on Kubernetes and automating event-driven insurance (P&C) workflows (claims/policy + fraud checks), reporting ~60% manual overhead reduction and ~99% uptime, with strong monitoring/drift-detection and business-facing Power BI reporting.”

Khoa Nguyen

Screened

Junior Software Engineer specializing in Python, AWS, and data/ETL systems

Washington, USA1y exp

“Data/ETL-focused engineer with Amazon experience building and deploying AWS-based pipelines that became the primary source of automated customer feedback insights (processing millions of records daily). Demonstrated strong incident troubleshooting across software/host/network layers using CloudWatch, traces, and metrics, plus hands-on stakeholder and on-site operator collaboration to translate reporting needs into star-schema data models and tailored Python ETL logic.”

Tabitha Wallace

Screened

Director-level Talent Acquisition & TA Operations leader specializing in scalable recruiting transformation

New York, NY14y exp

“Talent acquisition leader with experience managing recruiter/sourcer teams (7–13 direct reports) and partnering closely with HRBPs and executive stakeholders on workforce planning, org design, and compensation strategy. Drove measurable recruiting outcomes, including implementing HireEZ to modernize sourcing (18% time-to-fill reduction) and successfully staffing a large government contract requiring ~150 hires by influencing leadership to adjust below-market compensation.”

Hoai-Nam Hoang

Screened

Director-level People Operations & HR Business Partner specializing in scaling SaaS and media teams

10y exp

“People/HR leader with experience building analytics and product/engineering/design orgs and managing lean global teams across APAC/EMEA/NAMER. Notably helped scale Progyny’s engineering team 4x in under two years by implementing dual career paths and leveling frameworks, repositioning engineering as a strategic partner. Experienced in senior-leader change initiatives (e.g., return-to-office) with strong manager enablement and communication rigor.”

Eduardo Diaz

Screened

Senior Full-Stack Software Engineer specializing in Python, FastAPI/Django, and Azure

Remote13y exp

“Backend/data engineer with production experience building real-time IoT telemetry pipelines for wind/solar assets at Siemens (FastAPI on Azure Event Hubs/Service Bus, Cosmos DB + SQL Server) and deploying GPS/fleet telematics microservices on AWS ECS Fargate with Terraform and blue/green CI/CD. Demonstrated strong reliability and performance chops, including a 30s-to-<100ms SQL optimization and owning a Kafka pipeline incident resolved in ~20 minutes.”