Vetted Time Series Forecasting Professionals

Pre-screened and vetted.

DS

Junior Software Engineer specializing in Quantitative Finance and AI/ML

Dallas, TX2y exp
VWH Capital ManagementIndiana University Bloomington
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SP

Mid-level AI/ML Engineer specializing in LLM agents, search/recommendation, and MLOps

San Diego, CA5y exp
Events.comSan Diego State University
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SG

Mid-level Data Scientist specializing in ML, NLP and forecasting

Catonsville, MD3y exp
EnigmaUniversity of Maryland, Baltimore County
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SB

Mid-level Software Engineer specializing in AI/GenAI and cloud-native backend systems

6y exp
Stardust Science LabsUniversity of Central Missouri
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PJ

Mid-Level Software Engineer specializing in full-stack and backend systems

IL, USA3y exp
Motion Works Physical TherapyIllinois Institute of Technology
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AA

Mid-level Data Scientist specializing in Healthcare ML and Generative AI

Kansas City, MO5y exp
WestCareUniversity of Missouri-Kansas City
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AA

Junior Software Engineer specializing in GenAI and backend systems

Bloomington, Indiana2y exp
Project 990Indiana University Bloomington
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HT

Mid-level AI/ML Engineer specializing in LLMs, RAG, and agentic AI systems

Brooklyn, NY3y exp
CARA SYSTEMSNortheastern University
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BS

Mid-level AI/ML Engineer specializing in NLP, LLMs, and RAG systems

CA, USA5y exp
DXC TechnologyCalifornia State University, Long Beach
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HM

Junior Software Engineer specializing in full-stack AI/ML forecasting and embedded systems

San Jose, CA2y exp
Featurebox AICalifornia State University, San Bernardino
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PG

Mid-level AI/ML Engineer specializing in cloud AI, MLOps, and NLP

Washington, USA4y exp
iLink DigitalFlorida Atlantic University
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AR

Mid-level AI/ML Engineer specializing in MLOps and healthcare analytics

Houston, TX4y exp
Graviti EnergyUniversity of Texas at Arlington
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VM

Mid AI/ML Engineer specializing in NLP and generative AI

Saint Louis, MO3y exp
EpsilonSaint Louis University
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VP

Vikesh Patel

Screened ReferencesStrong rec.

Senior AI/ML Engineer & Data Scientist specializing in LLMs, RAG, and MLOps

Eagan, MN8y exp
Intertech, Inc.Metropolitan State University

ML/NLP practitioner who has delivered production systems in regulated domains, including a healthcare compliance pipeline using RAG (GPT-4/Claude) plus TF-IDF retrieval that increased document review throughput 4.5x. Also has hands-on experience improving fraud detection data quality via entity resolution (Levenshtein, Dedupe.py) validated with A/B testing, and building scalable, monitored workflows with Airflow, CI/CD, and AWS SageMaker.

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SR

Swapnil Ramanna

Screened ReferencesModerate rec.

Mid-level Data Scientist specializing in Generative AI and Healthcare Analytics

3y exp
AdvocateIndiana University-Purdue University

Built a LangGraph-based, tool-routing LLM chatbot to deliver fast, trustworthy investment-stock insights (including tariff impact) and deployed it to production on Snowflake after initially developing in Azure with AI Search and the Microsoft Agent Framework. Improved routing robustness by moving from LLM-based decisions to a deterministic router backed by schema-relationship graphs and YAML metadata, and ran the project iteratively with non-technical stakeholders over an 8-month engagement.

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AS

Adithya Sharma

Screened ReferencesModerate rec.

Mid-level AI/ML Engineer specializing in MLOps, NLP, and Generative AI

Remote, USA5y exp
EncoraUniversity of Michigan-Dearborn

Built and deployed a production LLM-powered text-to-SQL/document intelligence chatbot on AWS that lets non-technical business users query complex enterprise databases in plain English. Demonstrates deep practical expertise in schema-aware prompting, embeddings-based schema retrieval, SQL safety/validation guardrails, and rigorous offline/online evaluation with human-in-the-loop approvals for risky queries.

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HP

Hetal Pambhar

Screened ReferencesModerate rec.

Mid-level Data Engineer and Analytics Analyst specializing in business growth and marketing insights

Dallas, TX4y exp
Worldwide ExpressUniversity of North Texas at Dallas

Analytics professional with operations-grounded experience at WWEX Group who built a Snowflake/dbt fleet-efficiency data model combining telematics, ERP, and driver logs into near real-time executive reporting. They pair strong SQL/Python workflow automation with practical stakeholder enablement, and cite measurable impact including cutting reporting time from 72 hours to 15 minutes and helping drive $450K in quarterly fuel savings.

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SS

Mid-level AI Engineer and Data Scientist specializing in LLM agents and RAG systems

Palo Alto, CA5y exp
LemmataUniversity at Buffalo

Built a production-grade LLM evaluation and regression system that stress-tests models across hundreds of iterations, combining LLM-as-judge, semantic similarity, statistical metrics, and rule-based checks, with results delivered via stakeholder-friendly HTML reports and dashboards. Experienced orchestrating multi-agent RAG workflows using LangChain/LangGraph and event-driven GenAI pipelines in n8n integrating OCR, speech-to-text, and external APIs, with strong emphasis on reliability, observability, and explainable failures.

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SV

Mid-Level Full-Stack Software Engineer specializing in cloud-native apps and ML services

Bowling Green, OH4y exp
Senecio Software IncBowling Green State University

Software engineer who deployed and stabilized a real-time analytics platform at Senecio Software, focusing on production reliability, observability, and performance under load. Experienced debugging issues spanning distributed services and networking (e.g., tracing timeouts to packet loss from misconfiguration) and extending Python (FastAPI/Django) APIs for customer-specific analytics features in a configurable, maintainable way.

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NT

Mid-level AI Engineer specializing in ML, LLM applications, and data automation

Atlanta, GA4y exp
Exus Renewables North AmericaGeorgia State University

Data/ML practitioner who has built a production RAG-based knowledge assistant integrated into Microsoft 365/internal dashboards to help employees query internal documents in plain English. Experienced orchestrating and hardening ETL pipelines with Airflow and Azure Data Factory (validation, retries, monitoring) and running end-to-end model evaluation and production performance tracking via Power BI.

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