Vetted Power BI Professionals

Ryan Echols

Screened

Senior Workforce Analytics & WFM Leader specializing in contact center operations

Marietta, GA8y exp

“Operations-focused team lead currently managing 20 coordinators, with strong workforce management experience spanning forecasting, scheduling, KPI/staffing reporting, and executive-facing data presentations. Led a cross-functional Salesforce implementation and redesigned forecasting/workflow to support a newly created internal-promotion department, improving flexibility in coverage planning.”

“Worked on industrial pump analytics at SitePro, where they built an anomaly detector using messy sensor and pump data and used historical failure and maintenance cost analysis to make the business case to stakeholders. They combine SQL/Python data preparation with practical stakeholder communication around metrics like churn and operational impact.”

“Analytics candidate currently at Facteus with hands-on experience turning messy transactional data into trusted reporting layers in Snowflake and Power BI. They combine SQL and Python automation with strong validation, performance tuning, and stakeholder-facing metric design, including cohort-based retention and segmentation work that improved trust and adoption of analytics.”

“Healthcare analytics candidate with hands-on experience turning messy EHR, billing, and operational data into validated SQL datasets and automated Python/Airflow pipelines. They appear strongest in hospital KPI reporting—especially length of stay, readmissions, retention, and bed utilization—and have owned projects from metric definition through Power BI delivery and impact measurement.”

Cia Hang

Screened

Executive IT and Operations leader specializing in digital transformation and security

Chicago, IL13y exp

“Candidate is very familiar with the venture capital and broader investment landscape, but is not interested in founding a company. They have worked with several TPG-backed or TPG-owned organizations, helping drive business scaling, cost reduction, and execution against investor governance requirements.”

“Candidate has hands-on project experience in healthcare analytics, using SQL, Python, and Power BI to analyze CMS hospital readmissions and HRRP penalty risk in Florida. Their work centers on turning messy CMS flat files into reporting-ready datasets, benchmarking hospitals against national references, and surfacing financial risk through dashboards.”

“Healthcare analytics professional with Cigna experience turning complex claims, eligibility, and provider data into trusted reporting layers using SQL, Python, and Power BI. Stands out for combining deep data-quality rigor with end-to-end ownership of operational analytics projects, including standardized retention/churn metric design and automated reporting workflows.”

Vincent Osere

Screened

Senior Operations Analyst specializing in business intelligence and financial services

Massachusetts, USA15y exp

“Analytics-focused candidate with hands-on experience turning messy datasets into reporting-ready outputs using SQL, building reproducible Python workflows, and operationalizing metrics in R Shiny dashboards. They stand out for combining structured data analysis with NLP and segmentation in marketplace-style datasets such as Airbnb, real estate, and sports salary data to drive pricing, engagement, and demand insights.”

“Senior data scientist with ~5 years’ experience building production ML/NLP systems in finance (Wells Fargo) and deep learning for sensor analytics in connected vehicles (Medtronic). Has delivered end-to-end platforms combining time-series forecasting with transformer-based NLP, including automated drift monitoring/retraining (MLflow + Airflow) and standardized Docker/CI/CD deployments; achieved a reported 22% precision improvement after domain fine-tuning.”

Steven Fritsch

Screened

Principal Product Manager specializing in AI and document intelligence

New York, NY12y exp

“Enterprise product leader with significant experience turning AI experiments into scalable, workflow-native capabilities at Datasite, especially in high-stakes M&A environments. Stands out for combining strong AI product strategy with nuanced UX judgment, emphasizing trust, transparency, and human-in-the-loop design over flashy automation.”

“Long-tenured EdTech operator who joined LinkIt! as the third Data Analyst when the company had fewer than 40 employees and grew into a Data Quality Manager over 7+ years. Stands out for blending data operations leadership—ETL migration, reporting automation, process documentation, and training—with highly hands-on startup execution across office operations, hybrid work rollout, and crisis response during COVID.”

“Backend/microservices engineer (Java/Spring Boot, Kafka, Angular microfrontends) with Teradata experience building distributed analytics/query routing platforms and delivering 20–30% latency reductions through event-driven redesign and reliability hardening. Also built and shipped an end-to-end multimodal medical imaging AI feature (LLaVA/Mistral 7B + LoRA) with production guardrails like confidence-based human review, drift monitoring, and audit logs.”

“Strategic sourcing/procurement professional with experience at Gumpro and Micron leading indirect (MRO/CapEx) and critical component sourcing initiatives. Uses structured category strategy (spend/Kraljic/Pareto), RFX, risk management, and TCO/should-cost models; reports $10M+ savings and lead-time reduction from 60 days to 2 days while mitigating geopolitical/tariff exposure and strengthening supply resilience.”

“Software engineer/product owner who has led end-to-end delivery of AI and content-management platforms, including building RAG-based reliability improvements and migrating fragile systems to containerized AWS ECS/Kubernetes with Terraform-managed CI/CD. Experienced designing event-driven microservices (SQS/SNS/RabbitMQ), scaling queue consumers with autoscaling, and creating internal Python tooling to standardize data connectors (e.g., BigQuery/Airtable/internal APIs) to speed iteration.”

“Built and productionized an enterprise retrieval-augmented generation platform for internal knowledge over large unstructured corpora, emphasizing trust via strict citation/grounding and hybrid retrieval (BM25 + FAISS + cross-encoder re-ranking). Demonstrates strong scaling and cost/latency optimization through incremental indexing/embedding and index partitioning, plus disciplined evaluation/observability practices. Has experience operationalizing pipelines with Airflow/Databricks/GitHub Actions and partnering closely with risk & compliance stakeholders on auditability requirements.”

“BNY Mellon engineer who has built and operated production AI systems end-to-end: a LangChain/Pinecone RAG platform scaled via FastAPI + Kubernetes to 1000 RPM with 99.9% uptime, supported by monitoring and data-drift detection. Also deep in data/infra orchestration (Airflow, Dagster, Terraform on AWS/EMR/EC2), processing 500GB+ daily and delivering measurable reliability and performance gains, plus strong compliance-facing model explainability using SHAP and Tableau.”

“Growth/creative marketer from Esleydunn Games who uses Google Analytics to integrate cross-channel performance data (TikTok, YouTube, LinkedIn, Facebook) and run structured A/B tests on video ad length and layout. Reported reducing CPA by 20 per customer when leveraging YouTube and TikTok, and improved CTR through CTA/button placement testing and ongoing user-feedback loops (forum/WeChat topics).”

“Backend/platform engineer who owned a Python-based smart finance assistant backend, building async FastAPI microservices with PostgreSQL/Redis and deploying to AWS EKS via Docker/Helm and CI/CD (GitHub Actions, Jenkins). Strong in production reliability and migrations—implemented observability (Prometheus/Grafana), security (JWT RBAC), and executed a low-downtime monolith-to-microservices migration plus Kafka-based event streaming with ordering/retry/idempotency patterns.”

“Engineering/IT leader with 12+ years of people management and deep ERP ecosystem experience, including SAP S/4HANA and large-scale integrations (APIs/EDI/e-commerce). Managed an 11-person cross-functional team supporting multiple business domains and led process improvements like support-cycle/ticketing and documentation, plus regression test automation strategy driven by business-critical prioritization.”

“AI/ML Engineer with 4+ years of experience (Capital One, Odin Technologies) and a master’s in Data Analytics (4.0 GPA) who has deployed LLM/RAG systems to production for compliance/risk and document review. Strong in orchestration and MLOps (Airflow, Kubernetes, MLflow, GitHub Actions) and in tackling real-world LLM constraints like latency, context limits, and data privacy, with measurable impact (20%+ manual review reduction; 33% faster release cycles).”

“Built and shipped production generative AI/RAG assistants in regulated financial contexts (S&P Global), automating compliance-oriented Q&A over earnings reports/filings with grounded answers and citations. Experienced across the full stack—AWS-based ingestion (PySpark/Glue), vector retrieval + LangChain agents, GPT-4/Claude model selection, and production reliability (monitoring, caching, retries) plus rigorous evaluation and regression testing.”

“AI/LLM engineer with production experience in legal tech: built a GPT-4 + LangChain RAG summarization system at Govpanel that reduced legal case-file review time by 50%+. Previously at LexisNexis, orchestrated end-to-end Airflow data/AI pipelines processing 5M+ legal documents daily, improving ETL runtime by 35% with robust validation, monitoring, and SLAs.”

“Customer-facing data engineering professional who builds and deploys real-time reporting/dashboard solutions, gathering reporting and compliance requirements through direct stakeholder engagement. Experienced with Google Cloud IAM governance, secure integrations (encryption, audit logging), and fast production troubleshooting of ETL/pipeline failures with follow-on monitoring and automated recovery improvements; motivated by hands-on, travel-oriented customer work.”