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Vetted Data Science Professionals
Pre-screened and vetted.
Director-level IT infrastructure leader specializing in cloud, DevOps, and enterprise operations
Director of Engineering specializing in AI platforms, cloud modernization, and FinTech
Junior Software Engineer specializing in backend, cloud, and machine learning systems
Junior Data Scientist specializing in generative AI and time series forecasting
Senior Machine Learning Engineer specializing in Generative AI and Healthcare IT
Director-level AI and data science leader specializing in clinical data and analytics
Mid-level Machine Learning Engineer specializing in NLP, time-series forecasting, and edge AI
Mid-level Machine Learning Engineer specializing in MLOps and LLM/RAG systems
Mid-level Data Scientist specializing in ML, NLP, and forecasting across finance and retail
Mid-level Software Engineer specializing in AI and cloud data platforms
Executive technology and marketing leader specializing in digital transformation and e-commerce
Junior M&A and private equity origination associate specializing in consumer and industrial deals
Ramesh Ramanathan
Executive HR and IT consultant specializing in talent, operations, and AI-enabled business functions
“High-volume full-desk recruiter who specializes in driving difficult searches to close with tight process discipline. In one standout example, they filled a highly niche Swahili-speaking video journalist role in DC by moving beyond job boards and networking into diaspora communities nationwide, ultimately relocating and closing a candidate from Maine.”
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.”
Soumya Nayak
Mid-level Software Engineer specializing in cloud-native systems and AI automation
“Software engineer with hands-on experience shipping production AI agents and end-to-end ecommerce workflows. They built a customer support automation agent with strong guardrails and evaluation practices, then improved it post-launch using real user data to cut latency ~30% and token cost ~25%. Also drove a zero-to-one self-serve order modification product across React UI, backend services, and cross-functional alignment.”
Mid-level Data Scientist / Machine Learning Engineer specializing in NLP and computer vision
May Tar
Mid-level Growth Marketer specializing in GTM, funnels, and community-led partnerships
“Growth/partnerships operator in the creator ecosystem who runs creator-led GTM launches and brand collaborations (not yet a traditional gaming studio partnership). Has executed a baby wellness program launch using Facebook/TikTok/Instagram plus live Zoom Q&As and co-branded partnerships, and designed outcome-based email re-engagement loops to improve repeat engagement; helped drive a campaign that led to a SEA creator award.”
Raden Ananta
Senior QA Engineer specializing in test automation and FinTech
“QA tester with consulting experience focused on payment systems, including scenario testing and automation using QF-Test. Has a business-impact mindset (prioritizes revenue-critical end-to-end flows) and has surfaced high-severity defects that required source code changes; not yet experienced with console game testing or platform certification requirements.”
Allen Saunders
Senior DevOps/Solutions Engineer specializing in CI/CD, cloud platforms, and API integrations
“Solutions Architect with 5+ years leading pre- and post-sales engagements, focused on taking complex tooling from test/prototype to secure production through a structured discovery-to-deployment approach. Experienced in LLM workflow troubleshooting using tools like Langfuse/Gopher and in developer enablement via concise, hands-on workshops (e.g., Jenkins on Kubernetes at scale). Has navigated internal and external blockers to drive adoption and keep enterprise deals moving (including a Jenkins sale to Love's).”
Sai Bandaru
Mid-level Machine Learning Engineer specializing in fraud detection and LLM systems
“At FiVerity, built and deployed a production LLM/RAG-based Information Gathering Tool for credit union fraud analysts that generates auditable investigation summaries from verified evidence. Focused on high-stakes constraints—hallucination prevention, cross-entity leakage controls, compliance/PII-safe monitoring, and latency—while also shipping customer-facing agentic workflows using CrewAI and LangGraph in close partnership with fraud and compliance stakeholders.”
Anvith Reddy T
Mid-level AI/ML Engineer specializing in Generative AI and MLOps
“ML/AI engineer with hands-on ownership of fraud detection and investigator-assist systems, combining anomaly detection with RAG-based LLM summarization in production. Stands out for translating research ideas into reliable cloud-deployed workflows that improved precision to 92%, cut review time by 25-30%, and increased investigator throughput by roughly 30% while also building reusable Python infrastructure for team-wide velocity.”
TingYu Chou
Entry-level ML Systems Engineer specializing in LLM infrastructure and recommender systems
“Engineer with a mature, agent-oriented approach to AI-driven software development, using structured planning, TDD, and verification loops rather than ad hoc prompting. Has hands-on experience acting as a tech lead for multiple AI agents in an LLM intelligent routing project, coordinating implementation, testing, debugging, and edge-case review with strong attention to system tradeoffs.”
Alicia Geng
Entry-level AI/ML Engineer specializing in AWS MLOps and computer vision
“Built and shipped a production RAG question-answering system using LangChain/OpenAI, Docker, and FastAPI, then reduced hallucinations through disciplined retrieval tuning and constrained prompting. Also implemented a custom evaluation framework (QA-pair dataset) to measure faithfulness/relevance and deployed containerized ML microservices on AWS ECS/Fargate with ALB and rolling, zero-downtime updates.”
Ruturaj Dixit
Junior Data Scientist specializing in AI/ML and product analytics
“Applied ML/data scientist who has owned backend-heavy AI systems end-to-end, including a market-signal platform on FastAPI/AWS and rapid MVP delivery in medical computer vision. Particularly interesting for teams needing someone who can combine model development, backend APIs, production debugging, and pragmatic low-latency architecture decisions.”