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Vetted Predictive Modeling Professionals
Pre-screened and vetted.
Mid-level Machine Learning Engineer specializing in NLP, LLMs, and MLOps
Mid-level Data Analyst & ML Engineer specializing in GenAI, NLP, and cloud data pipelines
Mid-level DevOps Engineer specializing in multi-cloud Kubernetes and CI/CD automation
Director-level Enterprise Architect specializing in digital transformation, AI and cloud strategy
Principal Data Scientist specializing in Generative AI, LLMs, and ML platforms
Mid-level Data Scientist specializing in customer analytics, ML pipelines, and churn forecasting
Director-level Product Data Science leader specializing in experimentation and causal inference
Mid-level AI Engineer specializing in LLM agents, RAG, and enterprise GenAI
Intern Data Scientist specializing in NLP and Large Language Models
Mid-level AI Data Scientist specializing in financial risk, fraud detection, and NLP/LLM systems
Mid-level AI/ML Engineer specializing in MLOps, distributed ML, and RAG pipelines
Mid-level Data Scientist specializing in marketing analytics and scalable data platforms
Senior Data Scientist specializing in Generative AI, NLP, and MLOps
Senior Business Analyst specializing in small business lending and portfolio risk
JYOTHI N
Senior Data Scientist specializing in analytics, experimentation, and BI on AWS
“Data/ML practitioner focused on healthcare data quality and record linkage: analyzed 10M+ records, built anomaly detection and NLP-driven entity resolution, and automated AWS ETL/validation pipelines (Glue/Redshift/Lambda), cutting data errors by 40% and generating $500k in annual savings. Has hands-on experience with embeddings (Sentence Transformers/spaCy), FAISS vector search, and fine-tuning for domain-specific matching.”
Varaprasad Bathula
Intern AI/ML Engineer specializing in LLM applications and data infrastructure
“Hands-on LLM practitioner who built a production document-processing pipeline in Python, tackling long-document handling and latency with chunking/batching and a user-driven correction feedback loop. Experienced operationalizing AI workflows with Kubernetes (CronJobs, autoscaling, scheduled data cleaning and weekly retraining) and applying structured testing/evaluation (E2E, LLM-as-judge, HITL) while communicating solutions clearly to non-technical clients using visual diagrams.”
Murali Krishna Vempalli
Mid-level Data Analyst specializing in retention, churn, and customer analytics
“Analytics professional with experience across healthcare and fintech, including building SQL/Python data pipelines at Optum and owning a fraud detection initiative at Razorpay. Stands out for combining messy-data cleanup, reproducible analytics workflows, and stakeholder-driven metric design, with a reported 25% improvement in fraud detection while keeping false positives under control.”
Priyanshu Maurya
Mid-level Data Scientist specializing in insurance, finance, and healthcare analytics
“Built and productionized LLM-driven sentiment scoring for earnings call transcripts at Goldman Sachs, replacing legacy NLP to deliver a cleaner trading signal while managing latency/cost via batching, caching, and distilled models. Also implemented an Airflow-orchestrated fraud modeling pipeline at MetLife with drift-based retraining and SageMaker deployment, and has a disciplined evaluation/rollout framework for reliable AI workflows.”