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Vetted SciPy Professionals
Pre-screened and vetted.
Entry-Level Data & Business Analyst specializing in ML, dashboards, and SaaS customer success
Mid-level Machine Learning Engineer specializing in GenAI and RAG systems
Executive Technology Leader (CTO/VP) specializing in cloud-native SaaS and AI/ML
Junior Data Scientist specializing in NLP, OCR, and recommendation systems
Senior Full-Stack Engineer specializing in cloud-native microservices, data engineering, and GenAI
Senior Data Engineer specializing in cloud data platforms and streaming analytics
Mid-level Software Engineer specializing in Python backend systems and APIs
Senior Software Engineer specializing in cloud-native .NET microservices and GenAI
Mid-level AI Engineer specializing in LLMs, computer vision, and production ML systems
Mid-level AI/ML Engineer specializing in NLP, LLMs, and fraud/AML analytics
Mid-level Data Scientist specializing in ML, NLP, and forecasting across finance and retail
Mid-level Data Engineer specializing in cloud data pipelines and analytics (AWS/Azure)
Mid-level Data Engineer specializing in big data pipelines and cloud data platforms
Senior Data Scientist specializing in ML engineering and cloud analytics
Mid-level AI Engineer specializing in machine learning and generative AI
Mid-level Data Scientist specializing in ML, NLP, and LLM-powered analytics
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.”
Sai Amartya Maruth Mandadi
Mid-Level Python Full-Stack Engineer specializing in Financial Services
“Backend/platform engineer who owned an end-to-end financial data ingestion and validation system (Python/Django/FastAPI, Postgres, AWS), including large-file performance tuning, auditability, and CI/CD. Strong Kubernetes/EKS + ArgoCD GitOps practitioner and has delivered both Kafka-based real-time transaction streaming and a legacy on-prem stack migration to AWS (ECS Fargate, RDS, S3, Secrets Manager) with controlled cutovers and data consistency validation.”
Laxminarayana Yaga
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“Built and deployed a production RAG pipeline at PNC Financial Services to let risk/compliance analysts query millions of internal financial documents in natural language, reducing manual search and speeding regulatory validation. Demonstrates deep practical experience with large-scale document ingestion/OCR cleanup, retrieval performance tuning (hierarchical indexing, caching), and LLM reliability controls (grounding, citations, abstention), plus cloud orchestration on Azure and AWS.”