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Vetted Customer Segmentation Professionals
Pre-screened and vetted.
Senior Data Scientist specializing in Generative AI, NLP, and ML for banking and healthcare
Junior Data Scientist specializing in risk modeling, NLP, and predictive analytics
Mid-level Data Scientist specializing in LLMs and NLP for financial analytics
Senior Data Scientist specializing in AWS ML solutions for healthcare, telecom, and e-commerce
Mid-level Data Engineer specializing in cloud lakehouse and real-time streaming
Mid-level Data Analytics Engineer specializing in ETL pipelines and BI dashboards
Mid-level Business Analyst specializing in sales analytics and revenue strategy
Mid-level AI Engineer specializing in production LLM, RAG, and agentic AI systems
Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms
Sanjay Mamani
Executive Technology Leader specializing in enterprise data, AI, and cloud analytics
“25-year builder/operator who has scaled others' visions and led VC-backed startup incubation work (Saltmines). Built Bridgetree’s AI CoE from 0 to 1 and cites $20M+ measurable customer impact, with experience leading 110-person cross-disciplinary teams. Exploring a new venture idea (gotAgentic.ai) focused on agentic AI solutions such as AI-ready data prep, agentic SDLC teams, and front-office automation (scheduling/invoicing).”
Anvesh Reddy Narra
Mid-level AI/ML Engineer specializing in Generative AI, RAG, and MLOps
“Built a secure, on-prem/private GPT assistant to replace manual SharePoint-style search across thousands of policies/SOPs/engineering docs, using a production RAG stack (LangChain/LangGraph, FAISS/Chroma, PyMuPDF+OCR, vLLM). Implemented layout-aware ingestion (including table-to-JSON) and a multi-agent retrieval/generation/verification workflow with strong observability and compliance guardrails, delivering ~70% reduction in search time.”
Vardhan Are
Mid-level Data Analyst specializing in AWS-based ETL, churn analytics, and BI dashboards
“Data/ML practitioner with experience at Airtel and Lincoln Financial delivering measurable business outcomes: improved retention 15% via NLP sentiment analysis and cut response time ~25% using sentence-BERT + FAISS semantic linking. Strong in data quality/identity resolution (SQL + fuzzy matching) and in building production-grade Python workflows orchestrated with Airflow/AWS Glue, including validation and dashboard integration in Power BI.”
varshini yaganti
Mid-level Data Analyst specializing in financial and customer analytics
“Analytics professional with experience at KPMG and Robosoft Technologies, working across financial and customer engagement data. They combine SQL, Python, experimentation, and BI dashboards to turn messy multi-source data into decision-ready insights, including a pricing test that improved conversion rates by 9%.”
Nishchal Gante
Mid-level Data Scientist specializing in MLOps and Generative AI
“Robotics software/ML engineer who built perception and navigation-related ML systems for autonomous supermarket carts, including object detection, shelf recognition, and obstacle avoidance. Strong ROS/ROS2 practitioner who optimized real-time performance (reported 50% latency reduction) and deployed containerized ROS/ML pipelines at scale using Docker, Kubernetes, and CI/CD.”
Shree Gopalakrishnan
Entry-Level AI/ML Engineer specializing in LLM apps, RAG pipelines, and production ML systems
“AI/LLM practitioner at iFrog Marketing Solutions who drove a RAG chatbot from prototype to production in a legacy, AI-resistant environment by validating customer needs and building a business case. Implemented production-grade LLM practices (CI/CD eval gating, rollbacks, prompt/context engineering) and led internal workshops to bring non-AI-native developers up to speed while partnering with sales on tailored demos to drive adoption.”
Yogendra Nalam
Mid-level Data Scientist specializing in ML, NLP, and Generative AI
“GenAI/ML engineer with production experience at Cognizant and Ally Financial, building end-to-end LLM/RAG systems and ML pipelines. Delivered a domain chatbot trained from 90k tickets and 45k docs, improving intent accuracy (65%→83%), scaling to 800+ concurrent users with 99.2% uptime and sub-150ms latency, and driving +14% customer satisfaction. Strong in Azure ML + DevOps CI/CD, Dockerized deployments, and explainable/PII-safe modeling using SHAP/LIME to satisfy stakeholder trust and GDPR needs.”
Venus Tathgur
Senior Program/Project Manager specializing in telecom partner governance and Microsoft cloud security
“Lifecycle/CRM marketer with 14 years of cross-functional experience, leveraging SQL-driven segmentation and structured A/B/multivariate testing to optimize engagement and conversions. Has led coordinated national/regional launches for a hardware product and tracks impact through CRM campaign codes tied to closed sales.”
Matthew Melendez
Mid-level Data Scientist specializing in machine learning and analytics
“Data scientist with hands-on experience building an XGBoost-based customer segmentation/churn risk scoring model used by sales and marketing teams. Emphasizes production-grade practices—efficient SQL for large-scale data pulls, rigorous data validation/testing, and scalable, modular Python code designed to support multiple customer types.”
Rahul Setia
Director-level Growth Marketing leader specializing in full-funnel acquisition and lifecycle optimization
“Growth and partnerships professional with experience across fintech (SMB loans) and edtech (ByteLearn), combining SEO-led content ecosystems and performance marketing experimentation with rigorous lead-quality verification. Has closed white-label partnerships in the dental industry and built creator/referral incentive programs, consistently tying initiatives to funnel metrics like leads, MQL/SQL, activations, LTV, and ROAS.”
Alain Villalonga Martinez
Entry-level Data Engineer specializing in ETL, analytics, and anomaly detection
“Worked on industrial pump analytics at SitePro, where they built an anomaly detector using messy sensor and pump data and used historical failure and maintenance cost analysis to make the business case to stakeholders. They combine SQL/Python data preparation with practical stakeholder communication around metrics like churn and operational impact.”