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Vetted Data & Analytics Professionals
Pre-screened and vetted.
Popular Titles
Mid-level Data Scientist specializing in machine learning and analytics
Mid-level Data Analyst/Data Engineer specializing in machine learning and NLP
Senior Data Analyst specializing in BI, data engineering, and predictive analytics
Senior Data Analyst specializing in healthcare, insurance, and financial analytics
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics
Senior Product Manager specializing in B2B SaaS platforms and AI/ML features
Mid-level Data Engineer specializing in cloud ETL, streaming, and data warehousing
Mid-level Data Engineer specializing in cloud data pipelines and full-stack analytics
revanth polthi
Mid-level Data Scientist specializing in Generative AI and MLOps
“GenAI/LLM engineer with production experience at Allstate building an end-to-end document intelligence workflow for insurance operations—automating document intake, classification, and risk signal extraction. Emphasizes high-reliability design for regulated/high-stakes outputs using schema enforcement, confidence thresholds, validation rules, and human-in-the-loop routing, with metric-driven offline evaluation and production monitoring.”
Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines
Mid-level Data Engineer specializing in cloud data pipelines and streaming analytics
Senior Business Analyst / QA Lead specializing in cloud, security, and enterprise testing
Mid-level Data Engineer specializing in AWS data platforms and streaming pipelines
Senior Data Engineer specializing in AWS-based data pipelines and multi-tenant SaaS
Director of Architecture & Data Engineering specializing in enterprise data platforms
Mahesh Ponnam
Mid-level Data Scientist specializing in credit risk, fraud detection, and ESG analytics
“AI/LLM practitioner who has deployed production chatbots across e-commerce, HRMS, and real estate, focusing on retrieval-first workflows for factual tasks like product and property search. Optimized intent understanding and significantly improved latency by using lightweight embeddings and tuning the inference pipeline on Groq (Llama 3.3), while applying modular orchestration and measurable production evaluation.”
Dhanush Chandra Sekhar
Junior Data Engineer specializing in data pipelines and streaming ingestion
“Backend/data platform engineer who owned a near-real-time patient feedback ingestion system, building a FastAPI + Kafka service with Snowflake/Airflow orchestration. Demonstrates strong production Kubernetes/GitOps practices on AWS EKS (Helm, Argo CD, Sealed Secrets) and solved real-time data integrity issues via idempotent processing with Redis.”
bharath burgoju
Mid-Level Data Engineer specializing in cloud data pipelines and big data platforms
“Data engineer with ~4 years of experience building Python-based data ingestion/processing services and real-time streaming pipelines (Kafka/PubSub + Spark Structured Streaming). Has deployed containerized data applications on Kubernetes with GitLab CI/Jenkins pipelines and applied GitOps to cut deployment time ~40% while reducing config drift. Also supported a legacy on-prem data warehouse/backend migration to GCP using phased migration and parallel validation to meet strict reliability/SLA needs.”
Hemant Deshmukh
Mid-level Data Engineer specializing in cloud data pipelines and analytics engineering
“Built and deployed a production LLM-powered demand and churn forecasting system for an e-commerce client, combining open-source LLMs (LLaMA/Mistral) and Sentence-BERT embeddings to generate business-friendly explanations of forecast drivers. Strong focus on data quality and model trust (validation, baselines, segmented monitoring) and production reliability via Airflow-orchestrated pipelines with readiness checks, retries, and ongoing drift/A-B testing.”