Vetted Sentiment Analysis Professionals

Pre-screened and vetted.

MA

Executive CTO specializing in AI, cloud, and regulated SaaS platforms

St. Petersburg, FL19y exp
ALPHA7XUniversity of Gävle
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NM

Mid-level Data Scientist / ML Engineer specializing in LLMs and predictive analytics

4y exp
New York Life
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RS

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

Warrensburg, MO4y exp
Costco
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Mark Kemp - Director of Product Management specializing in FinTech and financial data platforms in Austin, TX

Mark Kemp

Screened ReferencesStrong rec.

Director of Product Management specializing in FinTech and financial data platforms

Austin, TX15y exp
Consero GlobalConcordia University Texas

Product leader in financial services who has built both customer-facing and internal AI-enabled products, including an award-nominated retirement plan platform that drove submissions from 40% to 98% in good order and unlocked a $10M revenue stream. Also built product process and team structure from the ground up at Consero, with experience applying AI/LLMs to workflow automation and reporting in complex, data-heavy environments.

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JK

Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems

Jersey City, NJ5y exp
JPMorgan ChaseSaint Peter's University
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VR

Mid-Level Software Engineer specializing in Java/Spring Boot microservices and cloud DevOps

NJ, USA5y exp
Goldman SachsStevens Institute of Technology
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JF

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

Remote5y exp
EmerjenceBoston University
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KP

Krishnapriyanka Ponnaganti

Screened ReferencesStrong rec.

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

Atlanta, GA4y exp
KKRGENAI Innovations LLCUC San Diego

ML/AI engineer with hands-on experience shipping production computer vision and GenAI systems, including a fabric defect detection platform that combined vision models with agentic LLM workflows to reach 89% human-inspector agreement at 200 ms latency. Also built a RAG-based code QA tool for developers and emphasizes production monitoring, evaluation, caching, and reusable Python service design.

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RG

Rithindatta Gundu

Screened ReferencesStrong rec.

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

San Francisco, CA4y exp
Wells FargoSeattle University

Built a production LLM-powered fraud detection platform at Wells Fargo, combining OpenAI/Hugging Face models with RAG-based explanations to make flagged transactions interpretable for risk and compliance teams. Delivered low-latency, real-time inference at high scale on AWS (SageMaker + EKS), with strong observability and security controls, reducing manual reviews and false positives in a regulated environment.

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JD

Jason Daniel

Screened ReferencesStrong rec.

Executive Restaurant Operations Leader specializing in multi-unit growth and turnarounds

Austin, TX14y exp
TacodeliTarrant County College

Operations leader with repeated startup/entrepreneurial experience building internal operating systems from the ground up—creating department-by-department SOP/policy manuals and implementing KPI-driven management. Strong in diagnosing issues via operational/financial data and rolling out scalable people systems (structured interviews, training/certifications, onboarding) with retention measured across 14/30/60/90-day cohorts.

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NG

Naga Gayatri Bandaru

Screened ReferencesModerate rec.

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

Cleveland, Ohio3y exp
Cleveland ClinicSan José State University

Backend/ML engineer who has shipped high-scale real-time systems across e-commerce and healthcare: built a PharmEasy real-time recommendation engine for ~2M monthly users (cut feature latency 5 min→30 sec; +15% cross-sell) and architected a HIPAA-compliant multimodal clinical diagnostic workflow (DICOM+EHR) with XAI, MLOps (MLflow/Airflow/K8s), and drift/monitoring guardrails supporting 10k+ daily predictions.

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JH

Joshua Hall

Screened ReferencesStrong rec.

Executive product leader specializing in AI-native platforms and design-first SaaS

Omaha, NE24y exp
Assembli AICreighton University

Co-founder and employee #1 who built Reva, a vertically integrated conversational CRM for multifamily leasing and resident services, leading product, engineering, and design from inception through acquisition. Combines deep enterprise product leadership with early AI experience, including a pre-LLM chatbot that drove a 400% lift in lead conversion and prior edtech work where AI-enabled learning tools improved struggling students by a full letter grade on average.

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VK

Vamsi Koppala

Screened

Mid-level Machine Learning Engineer specializing in Generative AI and RAG systems

Barrington, IL4y exp
ComericaTexas Tech University

LLM/ML engineer who has shipped an enterprise RAG-based Q&A system (LangChain/LlamaIndex, FAISS + Azure Cognitive Search, GPT-3.5/4 via OpenAI/Azure OpenAI) to production on Docker + Kubernetes/OpenShift, tackling hallucinations, retrieval quality, latency/cost, and RBAC/IAM security. Also partnered with operations leaders to turn manual reporting into an LLM-powered summarization and forecasting dashboard driven by real KPIs and iterative stakeholder feedback.

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VS

Senior Full-Stack Java Developer specializing in cloud-native microservices and real-time web apps

New York, USA5y exp
SeatGeekPace University

Full-stack engineer/product owner who built and scaled a customer-facing job application portal (Skillbridge) using TypeScript/React and Spring Boot/MongoDB, optimizing search performance with indexing, caching (Redis), and payload/lazy-loading improvements. Also built an internal AI-driven analytics dashboard for Salesforce operations using OpenAI sentiment analysis, achieving 70% reduction in manual analysis and driving adoption through demos and iterative feedback.

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PK

Parth Kasat

Screened

Mid-level Forward Deployed Engineer specializing in AI automation for finance and data platforms

Remote2y exp
ArganoGeorge Washington University

LLM/agentic workflow specialist with healthcare deployment experience who has taken LLM-based automation from prototype to production using operator-in-the-loop validation, RAG-style retrieval, RBAC, and monitoring for sensitive data compliance. Demonstrated real-time incident resolution (retrieval timeouts due to network/proxy misconfig) and strong GTM support—hands-on developer workshops and sales demos translating technical safeguards and real-time ETL into measurable ROI (70% ops reduction, ~$200K/year savings).

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NT

Nia Thompson

Screened

Senior HR Business Partner specializing in employee relations, global HR operations, and union environments

Hartford, CT8y exp
ConfidentialSierra College

People/HR leader specializing in change management, leader coaching, and people analytics—partnered with VP Operations and HR to execute a large-scale restructuring ahead of a major live event cycle with compressed timelines. Uses a systems-thinking, metrics-first approach (operational + engagement + adoption) and has resolved high-stakes ER conflicts involving retaliation allegations through neutral investigations and mediation.

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SK

Mid-level AI/ML Engineer specializing in Generative AI and healthcare data

NJ, USA6y exp
Johnson & JohnsonWichita State University

Built and deployed a production RAG-based document Q&A system on Azure OpenAI to help business teams search thousands of PDFs/Word files, using Qdrant vector search, MongoDB, and a Flask API. Demonstrates strong production engineering (streaming large-file ingestion, parallel preprocessing, monitoring/retries) plus systematic prompt/embedding/chunking experimentation to improve accuracy and reduce hallucinations, and has hands-on orchestration experience with ADF/Airflow/Databricks/Synapse.

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AB

Ananya Bojja

Screened

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

USA4y exp
CignaUniversity of New Hampshire

AI/ML engineer at Cigna Healthcare building a production, HIPAA-compliant LLM-powered clinical insights platform that summarizes unstructured medical notes using a fine-tuned transformer + RAG on AWS. Demonstrates strong end-to-end MLOps and cloud optimization (distillation, Spot/Lambda/Auto Scaling) with quantified outcomes (~28% accuracy lift, ~40% less manual review, ~25% lower ops cost) and strong clinician-facing explainability via SHAP and dashboards.

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SG

Mid-level Generative AI Engineer specializing in LLM systems and RAG

5y exp
Huntington BankCentral Michigan University

Currently at Huntington Bank, built a production-grade RAG system that helps business/operations teams get grounded answers from large volumes of internal enterprise documents. Owns ingestion and FastAPI backend, tuned hybrid BM25+vector retrieval and chunking for relevance, and evaluates reliability with metrics and observability (LangSmith, CloudWatch, Prometheus/Grafana) while partnering closely with non-technical stakeholders.

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Cristian Vega - Senior AI/ML Engineer specializing in Generative AI and RAG in California, null

Cristian Vega

Screened

Senior AI/ML Engineer specializing in Generative AI and RAG

California, null9y exp
Morf HealthUniversity of Texas at Austin

ML/NLP practitioner at Morf Health focused on unifying fragmented healthcare data by linking structured patient/encounter records with unstructured clinical notes. Has hands-on experience with transformer embeddings, vector databases, and domain fine-tuning, plus rigorous evaluation (precision/recall) and human-in-the-loop validation with clinical SMEs to make pipelines production-grade.

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Cary Burdick - Senior Data Scientist specializing in data engineering and analytics in Chicago, IL

Cary Burdick

Screened

Senior Data Scientist specializing in data engineering and analytics

Chicago, IL6y exp
USDAAuburn University

Data/NLP practitioner with experience in both financial services (Truist) and government (USDA), including an NLP-driven analysis of EU regulations to anticipate US regulatory focus and a major redesign/cleaning of complex pathogen lab-test public datasets. Built production data-quality pipelines with Dagster, Pandera, and Azure Synapse, and is comfortable validating hypotheses with historical backtesting and SME-driven quality controls.

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Nikitha Kommidi - Mid-level AI/ML Engineer specializing in fraud detection, NLP, and MLOps

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

6y exp
CitibankUniversity of Texas at Arlington

Built a production real-time fraud detection and customer-support automation platform at Citibank, tackling extreme class imbalance (reported ~1:5000) and strict latency constraints. Combines hands-on MLOps (Airflow, Kubernetes, MLflow; Snowflake/Spark/S3 integrations; CI/CD model promotion) with cross-functional delivery to Risk & Compliance focused on interpretability and reducing false positives.

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