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Vetted Data Analysts in Florida
Pre-screened and vetted in Florida.
Senior Data Analyst specializing in healthcare and financial analytics
Mid-level Data Analyst specializing in healthcare, e-commerce, and cloud analytics
Mid-level Data Analyst specializing in financial services analytics
Mid-level Data Engineer specializing in cloud data platforms and predictive analytics
Mid-level Data Analyst specializing in BI, ETL automation, and forecasting
Mid-level Data Analyst specializing in BI, analytics engineering, and KPI reporting
Mid-level Business Process & Data Analyst specializing in healthcare finance analytics
KasturiBharat Disale
Mid-level Business Analyst specializing in banking analytics and data engineering
“Analytics professional at Santander Bank with hands-on experience building SQL and Python workflows for transaction reporting, reconciliation, and monitoring across messy multi-source financial data. They combine strong data validation and exception-handling practices with stakeholder-friendly dashboards, and also bring digital analytics experience from a Google Analytics UI optimization project focused on funnel drop-off and engagement.”
Junior Data Analyst specializing in financial and healthcare data analytics
Principal Data Scientist specializing in NLP, LLM fine-tuning, and bioinformatics
Mid-level Data Analyst specializing in CRM and business intelligence analytics
Sai sri mylavarapu
Junior Data Analyst specializing in BI, ETL, and reporting
“Analytics professional with hands-on experience building SQL and Python workflows across SAP, Oracle, and internal operational systems, processing roughly 5 million records per month. They combine strong data quality rigor with stakeholder-friendly Power BI reporting, and cite a concrete impact of cutting reporting turnaround time from four days to two while surfacing cost anomalies for business teams.”
Samuel Charest
Mid-level Data Analyst specializing in marketing analytics and business intelligence
“Former Database Marketing Analyst with hands-on SQL experience supporting targeted casino marketing campaigns and a strong emphasis on validation accuracy. Also describes owning analytics work that standardized engagement metrics across teams, automated cohort/segmentation reporting, and helped identify onboarding friction that improved user engagement.”
Aaron Rodrigues
Junior Business & Data Analyst specializing in FinTech and banking analytics
“Analytics professional with Travelex experience spanning SQL ETL, Python-based machine learning workflows, and Power BI dashboarding in risk, fraud, and AML contexts. Stands out for replacing a $150K+ third-party compliance tool with internal dashboards and for materially improving operational efficiency through alert tuning, cutting alert volume by 50% and false positives by 60%.”
Mid-level Business Analyst specializing in BI, predictive analytics, and operations
Kalyani sai laxmi pallavi lakkoju
Mid-level Data Analyst specializing in BI, supply chain, and AI analytics
“Analytics-focused candidate with hands-on experience in both supply chain data and AI product analytics. They have built SQL and Python pipelines for messy ERP/inventory data as well as high-volume user event data, and have driven experimentation, retention measurement, and dashboarding for AI avatar and voice/image cloning features.”
Mid-level Data Scientist & AI Engineer specializing in NLP, computer vision, and MLOps
Ketan Kshirsagar
Mid-level Business Analyst specializing in data analytics and BI
“Healthcare analytics professional with hands-on experience turning messy claims, eligibility, and utilization data into validated BI-ready models using SQL and Python. They combine strong data engineering and KPI design skills with stakeholder-facing delivery, including Power BI prototyping, retention metric operationalization, and analyses that supported care management interventions and cost-control decisions.”
“ML engineer with hands-on experience building banking AI systems end-to-end, including a customer-targeting model that improved campaign response rates by about 10%. Also shipped a RAG-based banking FAQ/support feature with safety guardrails and production optimizations around retrieval quality, latency, and cost, plus reusable Python services that reduced duplicate work for other engineers.”