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Vetted Data Cleaning Professionals
Pre-screened and vetted.
Mid-level AI/ML Engineer specializing in LLMs, RAG pipelines, and cloud-native MLOps
Mid-level Data Scientist specializing in NLP, predictive analytics, and healthcare/enterprise SaaS
Junior Marketing & Operations Analyst specializing in performance analytics and retail merchandising
Senior Supply Chain Specialist specializing in inventory optimization and procurement analytics
Junior Mechatronics/Robotics Engineer specializing in computer vision and automation
Junior Full-Stack Developer specializing in web systems and performance-focused backend work
Mid-level Full-Stack GenAI/ML Engineer specializing in agentic AI and RAG systems
Mid-level QA/Systems Analyst specializing in test tooling, observability, and healthcare data migration
Mid-level AI/ML Engineer specializing in NLP, LLMs, and fraud/AML analytics
Mid-level Data Scientist specializing in NLP, risk analytics, and MLOps
Mid-level AI/ML Engineer specializing in risk modeling, NLP, and Generative AI
Mid-level Data Scientist specializing in ML, NLP, and forecasting across finance and retail
Junior Data & AI Analyst specializing in BI, LLM applications, and analytics
Mid-level Data Engineer specializing in cloud-native ETL/ELT and Snowflake analytics platforms
Mid-level Applied AI Engineer specializing in Generative AI and RAG systems
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics
Senior Data Strategy & AI Product Consultant specializing in analytics platforms and privacy-safe measurement
Bharath Reddy Nallu
Mid-level Machine Learning Engineer specializing in NLP and scalable MLOps
“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”
Pranali Redij
Marketing Analytics & Marketing Operations professional specializing in CRM and automation
“Lifecycle/CRM marketer with hands-on HubSpot expertise who improves funnel performance by fixing data foundations (workflow logic + validation), then building lifecycle segmentation, nurture sequences, and measurement dashboards tied to CAC/ARR. Has driven measurable lifts in data accuracy, early lifecycle engagement, and lead qualification through targeted messaging and A/B-tested email optimization across companies including Wicket and Beekind.”
Rodolfo Lopez
Senior Math Educator transitioning to Data Science & Business Analytics
“Recent McCombs School of Business (UT Austin) Post Graduate Program graduate in Data Science & Business Analytics with hands-on project experience spanning stock clustering/segmentation and hotel booking-cancellation prediction. Strong in end-to-end analysis workflows (EDA, cleaning, feature engineering) and rigorous model comparison/selection, with exposure to boosting methods and imbalanced-data techniques; limited experience so far with embeddings/vector databases and production deployment.”
Preetham Dandu
Junior Software Engineer specializing in backend, distributed systems, and cloud platforms
“MS candidate with strong backend/data engineering focus who builds research and data systems with production-grade rigor (reproducibility, observability, restartability). Has hands-on experience securing and scaling FastAPI-based gateways in front of Java microservices, leading SQL Server→Snowflake migrations with dual-write/feature-flag rollouts, and hardening Kafka-based fleet-tracking systems against out-of-order and duplicate events.”
Amit Prajapati
Junior Data Scientist / Software Engineer specializing in data pipelines and applied ML
“Built a production RAG chatbot for Worcester Polytechnic Institute that indexes 500+ webpages using FAISS + Llama 3, with strong grounding/hallucination controls (confidence thresholds and citations). Also has internship experience orchestrating multi-step ETL pipelines with AWS Step Functions and delivered a 30x faster fraud/claims triage workflow at Munich Re using association rules and stakeholder-friendly dashboards.”