Vetted Power BI Professionals

“Data engineer with experience at Capital One and HSBC building and operating GCP-based data platforms. Led an end-to-end Oracle-to-BigQuery migration processing ~200–300GB/day using Dataflow/Beam, Airflow, Dataproc/PySpark, and Looker, achieving ~99.5% pipeline success and ~30% fewer data quality issues. Strong in production reliability, schema drift handling for external APIs, and BigQuery performance/serving patterns (materialized views, authorized views, versioned datasets).”

Sukesh Anamaneni

Screened

Senior Business Analyst specializing in AI and commercial banking analytics

Detroit, MI5y exp

“Analytics candidate with hands-on experience supporting a workforce system transformation from symplr to Oracle Fusion Time and Labor, using SQL and Python to turn operational HR, attendance, and payroll data into reporting-ready datasets. They emphasize performance optimization, reusable analytics pipelines, and metric consistency across dashboards, with project work focused on overtime reduction, workforce efficiency, and retention trends by department.”

“Built and deployed a GenAI-powered PhD career intelligence platform at NYU that maps academic backgrounds to career paths and converts long academic CVs into job-ready resumes. Stands out for treating LLM systems as structured production pipelines—combining NLP extraction, embeddings, orchestration, and AWS deployment—to improve recommendation quality and cut resume preparation time by 70%.”

Dhriti Kanchan

Screened

Mid-level Data Analyst specializing in healthcare and financial analytics

Texas, USA5y exp

“Analytics-focused candidate with hands-on experience turning messy CRM, e-commerce, payments, and support data into trusted reporting datasets using SQL and Python. They have owned end-to-end churn and retention analytics work, including RFM-based segmentation, dashboard delivery, and metric standardization across sales, marketing, and finance.”

Waldorff Villacres

Screened

Healthcare technology executive and architect with 20+ years leading enterprise platforms and digital transformation.

Seattle, Washington, USA21y exp

“Healthcare-focused founder in the R&D stage building an EHR and clinical staffing startup centered on value-based care. They have already tested the concept with the market, are engaging Medicaid/Medicare leaders and industry conferences like ViVE and HIMSS, and are focused on early-signal detection to improve patient outcomes while lowering utilization costs.”

“Built and deployed a production RAG-based internal knowledge assistant that let analysts query company documents in natural language, using LangChain/LangGraph with Pinecone and a FastAPI service for integration. Emphasizes reliability in production through hallucination mitigation (retrieval tuning + prompt guardrails) and measurable evaluation/monitoring (accuracy, latency, task completion, hallucination rate), iterating based on user feedback.”

“Built an enterprise RAG-based document intelligence system at Freddie Mac for regulatory and financial documents, helping analysts cut search time from hours to minutes while improving retrieval accuracy by ~30%. Stands out for combining LLM product delivery with compliance-grade auditability, production monitoring, and scalable Python/FastAPI service design.”

“Management consulting and business development candidate with hands-on GTM, market research, and partnership expansion experience across high-growth organizations including OYO and IDP Education. Stands out for combining customer research, pricing and market models, and operational analytics to drive measurable outcomes like 200+ new locations, 15% revenue growth, and 14% margin improvement.”

“PMP-certified project/program manager with 13 years of experience leading high-stakes federal intelligence and law enforcement technology programs. Has owned a $15M+ portfolio spanning AI/ML analytics platforms, AWS/Azure cloud initiatives, and enterprise data integrations, with active Secret Clearance and a track record of improving executive visibility and reducing escalations in compliance-heavy environments.”

Jayakumar Velayutham

Screened

Director-level automotive strategy leader specializing in GTM, data, AI, and value creation

Plano, TX14y exp

“Automotive-focused GTM and strategy leader who built Kaizen Analytix's Automotive and Mobility practice from roughly $250K to $5M in recurring revenue by turning complex enterprise problems into repeatable offerings. Brings a rare mix of consulting, sales, operations, and delivery execution, with deep expertise in trade/tariff workflows and emerging AI use cases for automotive and mobility.”

Craig Bower

Screened

Executive operations leader specializing in PE-backed healthcare platform integration

New York Metro, USA8y exp

“Healthcare and multi-entity operations leader who progressed from managing infrastructure at NYU Langone to building enterprise operating systems across acquired businesses at True Ventures Group, and now serves as founding COO at NSCS. Stands out for combining hands-on integration execution with executive-level governance, including $12M budget ownership, $1.3M in savings, double-digit EBITDA growth, and centralized shared-services buildouts across clinical and care operations.”

“Backend engineer with experience evolving a high-volume agricultural loan processing platform (APMS) at HDFC Bank, emphasizing transactional integrity, auditability, and modularity while integrating with credit bureaus, document management, and risk engines. Also improved automation/reporting robustness at Trend Micro by catching duplicate-event retry edge cases and adding idempotency safeguards.”

“Customer-facing technical professional with experience supporting LLM/agentic-style workflows and complex integrated systems (APIs, backend logic, databases). Partnered with sales/customer teams at Radix Health to onboard new clients in phased prototypes, translating non-technical requirements into technical scope and implementing core product changes to tailor the appointment-booking solution for providers.”

“At KPMG, built and productionized a secure RAG-based LLM assistant that lets business and risk stakeholders query data warehouses in natural language, reducing dependence on data engineers for ad-hoc analysis. Demonstrates strong production rigor (Airflow orchestration, CI/CD, containerization), retrieval/embedding tuning (rechunking, semantic abstraction for structured data), and reliability controls (confidence thresholds, refusal behavior, monitoring and canary evals).”

“Open-source JavaScript contributor focused on performance and maintainability in data visualization libraries—refactored legacy ES5 into modular ES6, added tests/docs, and delivered ~30% faster load times with positive community adoption. Also optimized a React dashboard (~40% load-time reduction) and took ownership in an ambiguous AI product initiative by setting milestones, standing up an initial ML pipeline, and shipping a prototype in ~6 weeks that became the basis for production.”

“ML/GenAI engineer with production experience building an LLM-powered governance layer that summarizes verified drift/performance signals into validation reports and release notes, designed for regulated environments with de-identification and non-blocking fallbacks. Strong Airflow-based orchestration background across healthcare and finance, integrating Databricks/Spark and MLflow for scalable retraining/monitoring. Demonstrated ability to partner with non-technical healthcare operations teams to deliver actionable risk-scoring outputs via dashboards and automated reporting.”

“ML/LLM practitioner who has shipped production RAG systems (summarization + Q&A) and end-to-end Airflow-orchestrated demand forecasting pipelines at NEON IT. Strong focus on reliability—uses evaluation scripts, retrieval/chunking tuning, validation/retries/alerts, and stakeholder-driven iteration to make AI workflows consistent and usable.”

“Worked in a startup building an automated carbon accounting/climate reporting product, partnering with client IT and internal cross-functional teams to ship features and train end users. Also has software engineering internship experience debugging complex multi-workflow systems, including uncovering a significant (~20%) data annotation error by instrumenting and testing each workflow step.”

“Design engineer blending UX/product design with hands-on technical implementation and analytics. Built a full-stack restaurant web app (Node.js/MongoDB) and improved conversion via instrumentation (sensors/heatmaps) and UX changes; also designed a smart-meter anomaly triage dashboard using Python + Power BI to make complex data usable for non-analysts. Led trust-focused conversational UI direction for an AZ water chatbot based on deep user interviews.”

“Full-stack engineer with Bank of America experience modernizing a large-scale financial reporting platform. Built React frontends and Java/Spring Boot microservice APIs end-to-end, optimized data-heavy SQL performance (indexing/caching/pagination), and implemented an AI feature for forecasting and anomaly detection using Python/scikit-learn, with deployments supported on AWS.”

“Growth creative marketer who led end-to-end experimentation for Kahana’s Oasis agentic browser launch, repositioning it as a task-specific “productivity multiplier” and validating the message via structured A/B tests across Meta, LinkedIn, and landing pages. Reported performance lift included CPA reductions (23% Meta, 17% LinkedIn) and a 28% ROAS increase, with a repeatable modular framework for rapid creative iteration and hands-on direction of UGC creators and editors.”

“ML/GenAI engineer with recent CVS Health experience building a production RAG system over unstructured financial/research documents using LangChain, FAISS, and Pinecone, plus LoRA/PEFT fine-tuning of GPT/LLaMA for domain-aware summarization. Demonstrates strong applied MLOps and data engineering skills (Airflow/Prefect, Docker/Kubernetes, CI/CD, MLflow) and measurable impact (sub-second retrieval, ~40% better context retrieval, ~25% entity matching improvement).”

“Healthcare-focused data engineer/ML practitioner with experience at Lightbeam Health Solutions and Humana building production entity-resolution and semantic similarity pipelines across EMR, lab, and claims data. Uses NLP/ML (spaCy, scikit-learn, BioBERT/LightGBM) plus Snowflake/Airflow and vector search (Pinecone) to improve linkage accuracy (reported 90%) and semantic match quality (reported +12–15%), while reducing manual cleanup by 40%+.”

“Providing technical guidance to a small team exploring a biomedical startup focused on earlier disease detection, including for remote/underserved areas. The venture is in ideation with initial research completed and is moving toward prototyping while exploring initial investment/support.”