Vetted Predictive Modeling Professionals

“Full-stack engineer with fintech/trading domain experience (Fidelity) and startup SaaS CRM/billing platform work (Zoho), building real-time portfolio analytics and trade-processing systems. Strong in microservices, event-driven architectures (Kafka/WebSockets), and AWS/Kubernetes operations with measurable performance gains (~34–35% latency reduction) and maintainability improvements (~40% faster deployments). Targeting a founding full-stack engineer role in NYC with meaningful equity.”

“Data engineer at Capital One building AWS-based real-time and batch pipelines and backend data services for financial/fraud use cases. Has owned end-to-end pipelines processing millions of records/day, implemented dbt/Great Expectations quality gates, and tuned Redshift/Snowflake workloads (cutting query latency ~22–25% and reducing pipeline failures ~30–40%) while supporting 15+ downstream consumers.”

Yasser Ali

Screened

Junior AI & ML Engineer specializing in agentic systems and full-stack AI products

San Francisco, CA2y exp

“Won a machine learning contest and was placed onto a Kaiser data science team, where they built ML models for hospital bottleneck prediction and resource allocation. They later built and deployed a full-stack LLM-based “data analyst agent” (with custom orchestration plus LangChain/OpenAI Agents experience) that generates analysis code, answers questions, and produces dashboards from uploaded datasets, emphasizing rigorous evaluation sets, robustness, and healthcare security/compliance integration.”

Sandeep Athota

Screened

Mid-level AI/ML Engineer specializing in cloud MLOps and production ML systems

Texas, USA4y exp

“AI/ML engineer at J.P. Morgan Chase who deployed a production financial-risk prediction platform combining CNN/LSTM/gradient boosting on AWS SageMaker, with automated drift-triggered retraining and governance-grade fairness testing. Leveraged SageMaker Clarify plus SMOTE and LLM-generated synthetic data to improve minority-group F1 by 0.12, and communicated results to non-technical risk/ops teams via Power BI dashboards.”

Yukti Kamthan

Screened

Senior Software Engineer specializing in AI/ML and data systems

Mumbai, India10y exp

“Built and shipped production LLM/AI agent systems including an NL-to-SQL query agent with semantic search and Redis-based caching, using schema-aware prompting and threshold validation to reduce hallucinations. Has orchestration experience running ML microservices on Kubernetes and automating event-driven insurance (P&C) workflows (claims/policy + fraud checks), reporting ~60% manual overhead reduction and ~99% uptime, with strong monitoring/drift-detection and business-facing Power BI reporting.”

Barbara Christina Cruze

Screened

Senior Business Analytics Consultant specializing in BI, data engineering, and predictive analytics

Dallas, TX8y exp

“Healthcare analytics candidate with hands-on experience turning messy claims, enrollment, and reference data into trusted SQL reporting layers and reproducible Python workflows. They emphasize metric standardization, stakeholder alignment, and operational impact, including ~40% reduction in manual reporting effort and improved forecasting/resource prioritization through high-risk patient segmentation.”

“Analytics professional with experience across retail and healthcare, including Kroger and CVS Health. They have built SQL and Python workflows to clean and operationalize messy data, and have owned patient adherence/retention analytics projects that informed targeted interventions and improved refill and retention reporting.”

“ML/AI engineer with hands-on experience building production healthcare AI systems across predictive modeling and GenAI. They built an end-to-end patient risk prediction platform and a RAG-based clinical summarization feature, combining strong NLP/LLM skills with AWS deployment, monitoring, drift detection, and reusable Python service design to deliver measurable clinical and operational impact.”

“ML/AI engineer with strong production depth across classical ML, MLOps, LLM/RAG, and scalable Python data platforms, with experience at Cisco and Accenture. Stands out for tying technical decisions to measurable business outcomes, including $1.2M annual savings, 40% faster support resolution, and broad internal adoption of shared engineering frameworks.”

“Frontend engineer with JPMorgan experience shipping internal dashboards and real-time trading data interfaces. Stands out for a disciplined AI-assisted development workflow: uses AI selectively for boilerplate, rigorously reviews outputs against actual schemas and architecture, and has hands-on experience with React, GraphQL, WebSockets, Redux, and direct model API integrations.”

Richard Roberts

Screened

Executive TV/Film Editor-Producer specializing in reality, documentary, and broadcast programming

7y exp

“Senior video editor and post producer with deep Premiere experience (and Avid for network-style work), spanning feature documentaries, TV specials, promos, and music videos. Has led teams of 5–12 editors on high-volume schedules (5–6 shows/week) while mentoring on craft, software, music, and montage. Notable credits include work with Discovery and the YouTube channel Organic Nation (Stacey Poon Kinney).”