Vetted Data Analytics Professionals

“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”

Michael Forster

Screened ReferencesStrong rec.

Senior Data Engineer specializing in ETL/ELT pipelines and data integration platforms

New York, NY15y exp

“Data engineer/software engineer who led an end-to-end ETL/ELT pipeline at Pearson processing millions of rows of student data nightly, including client-side data prep/validation, SFTP/API ingestion, staging-based SQL validation/transforms, and production loading. Built reliability features like configurable per-client validation thresholds, detailed reporting, concurrency throttling via a custom queue, and multi-source merge/backfill logic to keep nightly loads running even when sources fail.”

“Operations leader from a hospital environment who manages distributed, multi-shift teams and applies product/analytics thinking to workflows and patient-care services. Partnered with senior leadership on major safety and emergency-preparedness changes (lockdown and disaster protocols) and has experience operating in a rapidly scaling healthcare organization (noted expansion to 26 hospitals in a year).”

“Paid media performance marketer with hands-on ownership of a $100K/month higher-education account spanning LinkedIn, Google Ads, and programmatic display/video. Built a structured 6-week experimentation approach (2-week test intervals) and used geo-fencing to reach military audiences, exceeding attendance goals for online MBA informational sessions (avg ~45 attendees vs 30 target). Strong in diagnosing stalled performance and translating complex metrics into client-friendly insights.”

“AI startup co-founder and CTO who helped raise $2.6M in seed funding at RedRex and drove product strategy from ideation through execution. Experienced with rapid experimentation and AI-driven prototyping to validate ideas quickly, and has direct exposure to the VC/accelerator ecosystem (Gener8tor) with a market-first approach to building and pitching startups.”

Ajay Rajakumar

Screened

Mid-level Full-Stack Developer specializing in Angular, Java, and MERN

Chennai, India4y exp

“Full-stack developer with 4 years of experience and an MS in Computer Science who led frontend delivery for a large airline platform (booking, check-in, and payment flows) using Angular/TypeScript with a Java backend. Emphasizes quality at scale via SonarQube monitoring, E2E/regression testing, and iterative Agile collaboration with clients using Figma.”

“Outbound-focused candidate coming from a Cushman & Wakefield internship where they built pipeline by prospecting potential office tenants through email, calls, and LinkedIn. They stand out for signal-based, highly personalized outreach to mid-market and enterprise stakeholders, with experience generating 2-4 qualified tours per week and thinking like a founding SDR around ICP design, account tiering, and repeatable cadence building.”

Nathan Holmes-King

Screened

Junior Data Scientist and Full-Stack Developer specializing in healthcare and matching systems

Iceland4y exp

“Solo builder developing their own app and using generative AI tools like Codex to both troubleshoot and write code. They taught themselves React and React Native over the past year through hands-on AI-assisted development and handle all technical work independently.”

“Full-stack engineer who built an end-to-end low-code/no-code IDE for creating AI/ML workflows for industrial IoT sensors using Next.js/TypeScript and NestJS microservices. Focused on scaling high-volume sensor dashboards—improved UX and performance via WebSockets, debouncing, pagination, and API payload reduction—validated with profiling tools and user feedback in a startup environment.”

Manvi Panjwani

Screened

Mid-level Machine Learning Engineer specializing in cloud, governance automation, and distributed systems

San Francisco, CA4y exp

“Governance engineer intern at GSK who built policy-as-code automation using Open Policy Agent/Rego integrated into GitHub CI/CD and Terraform workflows. Also built and shipped a voice-enabled expense tracking app using speech-to-text + LLM structured extraction with strong validation, retries, and semantic guardrails, and designed the supporting PostgreSQL data model with performance-focused indexing.”

Alankrit Srivastava

Screened

Intern Data Engineer specializing in Snowflake pipelines and AI/ML analytics

Houston, TX3y exp

“Built and operated an end-to-end TypeScript/Node AI agent platform for high-volume financial data that generates explainable investment signals and automates execution via resilient Playwright browser automation. Uses Postgres + pgvector/Prisma for RAG retrieval, Redis for async orchestration, Zod-based boundary validation as a circuit breaker, and OpenTelemetry for tracing/latency monitoring; also designed a TypeScript SDK with semver, scoped bearer-token auth, CLI key rotation, and interactive Swagger docs.”

“Serial founder/engineer who has raised capital for two prior startups and is now building a mental awareness venture. Drove rapid early traction for Fashom after an organic YouTube unboxing sparked demand, then scaled using influencer-led growth with no paid ads for ~2 years, achieving ~150% YoY growth and staying profitable through COVID.”

“Creator-led growth and digital marketing professional with experience as a media team lead and agency-side marketer (Furst spark), sourcing and negotiating creator partnerships for events, fintech apps, and lifestyle subscription launches. Runs data-driven, cross-platform campaigns (Instagram, TikTok, YouTube Shorts, Twitter/X) with trackable links and rapid optimization; reports doubling engagement rate in a fintech acquisition experiment and driving repeat creator collaborations.”

“LLM/MLOps engineer who has shipped a production RAG-based technical documentation assistant (FastAPI) cutting manual review by 45%, with deep hands-on retrieval optimization in Pinecone/LangChain (HNSW, hybrid + multi-query search, caching). Also brings healthcare domain experience—building Airflow-orchestrated EHR pipelines and delivering FDA-auditability-friendly predictive maintenance solutions using SHAP/LIME explainability surfaced in Power BI.”

“Full-stack engineer who built an oil & gas analytics dashboard backend using FastAPI, MongoDB, and Redis with a metadata-driven design for dynamic plotting. Shipped an LLM-powered chatbot (LangChain + tool/function calling) to let engineers query analytics in natural language, and also built a multi-step university chatbot workflow with Azure logging, confidence scoring, and human-in-the-loop review.”

AneeshReddy Kusa

Screened

Junior Full-Stack Software Engineer specializing in React and FinTech

Hyderabad, India2y exp

“Full-stack engineer with banking-domain experience (Cognizant/Kotak) building and optimizing high-usage transaction/account APIs on Spring Boot/Node/PostgreSQL in AWS/Docker, including peak-load performance fixes. Also built an end-to-end retail demand-forecasting feature during a master’s program, spanning data pipelines, ensemble models, dashboards, and operational guardrails like validation and fallbacks.”

PAVEL A ASPIAZU

Screened

Senior Paid Media (SEM/PPC) Manager specializing in Google Ads and Meta performance marketing

McLean, VA26y exp

“Paid media performance marketer with agency experience owning a high-spend account for ArcPoint Labs, running multi-channel Google Ads (search/display) and Meta campaigns to drive medical testing appointments and sales. Reported lifting ROAS from ~2x to ~6–7x within ~18 months while supporting expansion from 30 to 60 U.S. locations, using disciplined attribution, constant A/B testing, and structured campaign health audits.”

Snehitha Penumaka

Screened

Mid-level AI/ML Engineer specializing in predictive modeling and cloud ML pipelines

Dallas, TX3y exp

“LLM engineer/data engineer who has deployed production RAG systems for internal-document Q&A, building end-to-end ingestion, embedding, vector search, and FastAPI serving while actively reducing hallucinations and latency through rigorous retrieval tuning and caching. Also experienced in orchestrating cloud data pipelines (Airflow, AWS Glue, Azure Data Factory) and partnering with non-technical business teams to deliver AI solutions like automated document review.”

“Former Database Marketing Analyst with hands-on SQL experience supporting targeted casino marketing campaigns and a strong emphasis on validation accuracy. Also describes owning analytics work that standardized engagement metrics across teams, automated cohort/segmentation reporting, and helped identify onboarding friction that improved user engagement.”

“Software engineer with experience at Wipro Technologies and Wells Fargo building React-based SPAs, reusable component libraries, and developer documentation. Demonstrated strong performance engineering (React.memo, list virtualization, code splitting) with reported >50% rendering-time improvement, plus hands-on production support by diagnosing API outages via monitoring/logs and implementing traffic/server fixes. Comfortable leading workstreams in fast-changing environments using Kanban and tight stakeholder feedback loops.”

“Software/ML engineer who built a production automated job-finding and cold-email personalization system for Fortune 500 outreach, using JobSpy for dynamic scraping, LangChain orchestration, and LLM+vector DB semantic search with grounding/relevance metrics and guardrails. Also delivered a predictive investment analytics platform for financial advisors, communicating results via Tableau dashboards and portfolio KPIs like Sharpe ratio and drawdowns.”