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Vetted Power BI Professionals
Pre-screened and vetted.
Shashank Bijarapu
Mid-level AI/ML & Data Engineer specializing in MLOps and cloud data pipelines
“AI/ML engineer (Merkle) with hands-on experience deploying RAG-based LLM applications and real-time recommendation engines into production. Strong in cloud/on-prem architectures, GPU autoscaling, caching, and network optimization—delivered measurable latency reductions (40–70%) and improved retrieval relevance by systematically benchmarking chunking/embedding configurations and validating pipelines via CI/CD.”
Yash Namdeo Nikhare
Mid-level Machine Learning Engineer specializing in data security and GenAI systems
“Built Hexagon’s production Text-to-CAD Copilot that converts text and rough sketches into editable CAD code, combining GraphRAG (Neo4j/LangChain) with a Gemini-powered vision module and multi-agent geometric validation—cutting manual modeling from a day to ~45 seconds and driving retrieval latency below 50ms. Also has large-scale GCP data/ML orchestration experience (Airflow/Cloud Composer, Dataflow, Pub/Sub, Snowflake) processing 50M+ daily records with drift monitoring and automated reliability controls.”
Leelakarthik Devisetty
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and MLOps
“Data professional with ~4 years of experience, most recently at AIG (insurance), building ML/NLP systems for fraud detection and policy automation using transformers, CNNs, and clustering/anomaly detection. Also developed a RAG-based knowledge retrieval system, iterating across embedding models and moving to production based on precision and latency SLAs, then containerizing and deploying with SageMaker and CI/CD.”
Shraddha Yadav
Mid-level Strategic Sourcing & Procurement professional in global apparel manufacturing
“Decathlon sourcing/procurement professional managing end-to-end materials and components sourcing for multiple sportswear lines, spanning vendor selection, cost negotiation, production execution, and delivery. Known for building SOPs and performance dashboards to drive 98%+ OTIF, eliminating air freight entirely, and delivering ~5% seasonal cost savings. Also led supplier quality accountability (zero fabric rejections in 2 seasons) and advanced sustainability initiatives like the "No Coal 2025" transition via collaborative pilots.”
PRAHARSHA JANDHYALA
Mid-level Data Scientist/Data Analyst specializing in ML, BI dashboards, and ETL pipelines
“Data/ML practitioner with experience at Humana and Hexaware, focused on turning messy, semi-structured datasets into production-ready pipelines. Built an age-prediction model from book ratings using heavy feature engineering and multiple regression models, and has hands-on entity resolution (deterministic + fuzzy matching) plus embeddings/vector DB approaches for linking and search relevance.”
Prashanth Kedri
Mid-level Machine Learning Engineer specializing in MLOps, NLP, and predictive maintenance
“ML engineer with General Motors experience deploying production AI systems, including a BERT-based sentiment classifier for over a million customer support call transcripts (reported ~91% precision) and sub-200ms latency via FastAPI/Docker optimization. Also built predictive maintenance models and automated retraining/monitoring workflows using Airflow and MLflow, collaborating closely with non-technical customer support stakeholders.”
Erik Arriaga
Mid-level Data Engineer specializing in cloud data pipelines and machine learning
“Experience spans college-built AWS-hosted Python/Flask web apps and enterprise data work at General Motors, including PostgreSQL query optimization on millions of records and multi-tenant-style data isolation using group-based, column-level permission grants. Also built an AWS-hosted meat price prediction dashboard using Dash/Plotly and ran large nightly data pipelines orchestrated with Apache Airflow.”
Rakesh Thota
Mid-level Data Engineer specializing in multi-cloud real-time data pipelines
“Data engineer with healthcare/clinical trial domain experience who owned a 100TB+/month AWS pipeline end-to-end (Glue/S3/Redshift/Airflow) and drove measurable outcomes (20% lower latency, 99.9% reliability, 40% less manual reporting). Also built production data services and API-based ingestion on GCP (Cloud Run/Functions/BigQuery) with strong validation, versioning, and safe migration practices, and launched an early-stage RAG solution (LangChain + GPT-4) for researchers.”
Gopichand Muppaneni
Mid-level Data Engineer specializing in Azure, Spark, and scalable ETL/ELT pipelines
“Data engineer with banking FP&A experience who led an end-to-end migration of 10+ TB from Teradata to Azure (ADF + Data Lake + Databricks/PySpark + Synapse). Emphasizes reliability (multi-stage validation, monitoring/alerts) and performance (Spark tuning, incremental loads, autoscaling), reporting ~99.5% pipeline reliability while supporting downstream consumers with stable schemas and clear change management.”
Lerone Pieters
Senior Data Engineer specializing in cloud data platforms and real-time analytics
“Data/analytics engineer focused on finance and e-commerce integrations, building end-to-end pipelines and services across Odoo, QuickBooks, Snowflake, and Tableau. Replaced a costly third-party Walmart connector with a serverless AWS Lambda pipeline deployed via Terraform/GitHub and monitored with CloudWatch/Datadog, and shipped a bi-directional Odoo↔QuickBooks invoice sync with distributed locking plus Slack-based finance approvals.”
Saiprasad Barkam
Mid-level Data Engineer specializing in cloud ETL and streaming data pipelines
“Data engineer in healthcare/clinical data platforms (HarmonCare) who built and operated an end-to-end lakehouse pipeline ingesting HL7/FHIR at ~2–3M records/day on AWS (Glue/Lambda/S3/Spark) and serving trusted datasets in Snowflake. Implemented strong validation/reconciliation gates and a data quality framework that reduced discrepancies ~40%, plus CI/CD (GitHub Actions/Terraform) and monitoring (Airflow/CloudWatch).”
Sachin Dulla
Mid-level AI/ML Engineer specializing in NLP, fraud detection, and MLOps
“Built and deployed a domain-specific LLM chatbot for research/support, cutting manual effort by ~50%. Demonstrates strong applied LLM engineering: RAG, prompt grounding with citations and fallbacks, embedding/top-k tuning, and production monitoring (confidence, latency, feedback loops). Experienced orchestrating agent workflows with LangChain-style pipelines and continuous evaluation to maintain reliability.”
Bhavishyasai Chigurupati
Mid-Level Data/ML Engineer specializing in Generative AI and cloud data platforms
“Built and productionized an LLM-based financial document analysis system using a RAG pipeline, including robust ingestion/chunking/embedding workflows, vector DB retrieval, and an AWS-deployed FastAPI service containerized with Docker. Demonstrates strong applied expertise in improving retrieval quality and latency at scale, plus hands-on experience debugging agentic/LLM workflows with monitoring and trace-based analysis while supporting demos and customer-facing adoption.”
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%.”
Shreya Reddy Palla
Mid-level Business Analyst specializing in healthcare data and application consulting
“Analytics professional with University of Florida experience in occupational health reporting, including bloodborne pathogen and needlestick exposure programs. Stands out for turning messy healthcare operational data into trusted, analysis-ready reporting assets using SQL and Python, while partnering closely with stakeholders to define reliable metrics and improve operational oversight.”
Bryan Jones
Mid-level Data Analyst specializing in analytics, budgeting, and sports data systems
“Baseball advisor/recruiter with a player-development lens shaped by his own injury experience, combining TrackMan-driven analytics with deep coach and program relationships. He has helped athletes navigate high-stakes draft, rehab, and college decisions, including identifying under-scouted talent like John Klein and supporting his path to the Twins' 40-man roster.”
Sai Mekapothula
Mid-level Business Analyst specializing in healthcare data and reporting
“Worked on a CVS Health project transforming large healthcare claims data from databases and APIs into clean reporting tables and Power BI dashboards. Brings hands-on experience in SQL, Python automation, data validation, and stakeholder-driven metric definition for analytics workflows.”
VAMSI PULLAGURA
Mid-level Workday Analyst specializing in HCM, payroll, integrations, and reporting
“HRIS/payroll and compensation professional with strong Workday expertise spanning end-to-end U.S. payroll, compensation cycle support, and cross-functional reconciliation with finance. Stands out for building practical controls and Excel-based audit tools that catch issues early, including resolving integration failures and uncovering a ~$25K payroll/GL variance before close.”
Arslan Javed
Senior Machine Learning Engineer specializing in LLMs, NLP, and computer vision
“Built and owned production GenAI systems for both infrastructure automation and customer support. Most notably, they created a self-healing multi-cloud incident response system that automated 65% of tier-1 alerts and reduced application crashes by 75%, and also shipped a hybrid RAG support triage agent that automated 60% of tier-1 inquiries with human escalation guardrails.”
SaiSindhu Beeravolu
Mid AI/ML Engineer specializing in LLMs, RAG, and healthcare AI
“Healthcare ML/AI engineer with production experience at UnitedHealth Group, including an end-to-end readmission prediction system built on 50M+ patient records that improved accuracy by 18% and reduced preventable readmissions by 12%. Also shipped a clinically grounded LLM/RAG referral generator with human-in-the-loop safety controls, showing strong depth in regulated, high-stakes AI systems.”
“Built and owned a production RAG-based conversational AI system at Entera for real estate analysis, taking it from experimentation through AWS deployment, monitoring, and iterative improvement. Demonstrates strong practical judgment in retrieval design, LLM safety, and scalable Python service architecture, with measurable impact including 30-40% reduction in manual analysis time and roughly 30% better response accuracy.”
Tarun Abhaye Thiagarajan
Mid-level Solutions Architect specializing in Enterprise AI and SaaS
“Enterprise implementation/deployment specialist focused on HRMS and payroll systems across APAC customers, combining cloud/hybrid (AWS/Azure/GCP) integration work with strong client-facing delivery. Demonstrated ability to debug complex production issues across application, database, and network layers (e.g., isolating VPN/router congestion) and to tailor Python-based data cleaning/scoring/utilities to customer-specific workflows.”
SUMANTH Metimath
Mid-level Data Scientist specializing in ML, LLMs, and AI systems
“Candidate takes a pragmatic approach to AI-driven development, using AI as a productivity and learning aid while emphasizing personal understanding and code validation. They have hands-on experience applying AI-assisted workflows to a resume analysis and ATS scoring project, including code generation, debugging, parsing logic improvement, and testing.”
Raj Shrinivasan
Principal AI Engineer specializing in agentic systems and cloud-native platforms
“Built a production RAG-powered analytics copilot at Aya Healthcare for operations leaders and analysts on a large healthcare staffing platform processing over a billion telemetry records annually. Stands out for strong production-minded agent engineering: deterministic orchestration, grounding-first design, deep observability, and data-driven workflow changes such as confidence-based human review for a PR review agent.”