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Vetted R Professionals

Pre-screened and vetted.

RPythonSQLDockerAWSTensorFlow
NC

Nachiket Chavan

Screened

Mid-level Supply Chain Planner/Buyer specializing in sourcing, MRP, and analytics

Boston, MA4y exp
ASMPTNortheastern University

“Supply chain/sourcing professional focused on semiconductor tooling NPI ramp-ups, owning vendor selection through production and delivery. Demonstrates strong cost and trade-risk mitigation (e.g., avoided 25% Section 301 tariff via HTS/landed-cost analysis) and measurable supplier performance turnarounds (OTD improved to 95%) using SAP MRP, shortage analysis, and structured supplier governance.”

NegotiationForecastingInventory ManagementRegulatory ComplianceProject ManagementBudget Management+99
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SD

Sanya Dod

Screened

Junior Software Engineer specializing in AI/ML and verification

West Lafayette, IN2y exp
WISE Lab, Purdue UniversityPurdue University

“Embedded/real-time robotics-style engineer with hands-on STM32 development, sensor integration, and low-level drivers, focused on deterministic control behavior. Demonstrated systematic debugging of jitter/latency by instrumenting the sensing-to-actuation pipeline and eliminating blocking via interrupts, hardware timers, and DMA; also designs asynchronous, message-based interfaces for distributed real-time components. Familiar with ROS/ROS2 concepts (nodes/topics/callbacks) though not yet deployed a full production ROS system.”

PythonJavaCC++SQLR+78
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NK

NEHA KOLAN

Screened

Mid-Level Software Engineer specializing in microservices and cloud data pipelines

Texas, USA4y exp
CignaUniversity of North Texas

“Full-stack engineer with end-to-end ownership across React/TypeScript frontends, Spring Boot/Node microservices, and production ops on Docker/Kubernetes and AWS (ECS/CloudWatch). Built real-time healthcare eligibility and analytics systems at Cigna and an early-stage seller onboarding platform at Flipkart, driving measurable performance gains (35–40% latency/throughput improvements) through event-driven Kafka pipelines, Redis caching, and strong reliability/observability practices.”

A/B TestingAmazon RedshiftAmazon SageMakerAnomaly DetectionApache AirflowApache Kafka+122
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JS

Jitesh Sharma

Screened

Mid-level Growth Marketing Manager specializing in performance creative and marketing analytics

Mumbai, India3y exp
MirumUniversity of Texas at Austin

“Paid social creative lead with experience across major consumer brands (Duracell, Amazon Groceries, Puma) and Gen Z-focused retail, owning end-to-end creative strategy from concept/briefing and UGC direction through QA and delivery. Known for contextual, seasonally-timed campaigns and performance-driven iteration (CPA/ROAS, funnel drop-offs), including a Duracell Meta campaign that reached 20M+ views and sustained engagement gains via creator feedback loops.”

Video EditingMeta AdsTableauPower BISQLPython+66
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SS

Saffinah Shi

Screened

Junior Software Engineer specializing in full-stack, cloud serverless, and AI systems

Los Angeles, US2y exp
CoreSpeedNorthwestern University

“SDE who worked on an MGICS Lab robotics project building a multi-agent model to help agents understand tasks and generate robot instructions, emphasizing task-splitting, checking, and a reflection agent to improve accuracy. Also has experience using GitHub with automated CI/CD pipelines.”

API GatewayAWSAWS IAMAWS LambdaBERTCI/CD+133
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JB

Jahnavi Bellapukonda

Screened

Mid-Level Software Engineer specializing in full-stack web and cloud systems

Remote, USA3y exp
AdobeTexas Tech University

“Full-stack engineer with strong data engineering and privacy-domain experience, having owned an automated Data Subject Rights (DSR) processing pipeline end-to-end across Azure SQL and GCP (GCS/BigQuery). Emphasizes production reliability via idempotency, validation checkpoints, structured logging/monitoring, and safe CI/CD-driven deployments, and has also built React+TypeScript + Node/Postgres web apps with scalable, maintainable architecture.”

JavaMicroservicesSpring BootObject-Oriented Programming (OOP)PythonMultithreading+170
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PT

Phillip Taylor

Screened

Principal Data Strategy & Data Management Leader specializing in enterprise governance and analytics

Woodstock, IL25y exp
Taylored ConsultingSouthern Illinois University

“Operator/program leader with experience building operating models and execution cadences for data/analytics and energy data services across Entech, HealthEquity, and RealPage. Has launched an undefined energy data management service into regulated enterprise environments and driven cross-functional alignment via dashboards, SLAs, and OKRs—contributing to enterprise wins and a successful company sale.”

Data governanceData analyticsDashboardingData qualityETLDevOps+94
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MG

Mounika Gunturu

Screened

Senior Python Full-Stack Developer specializing in cloud-native microservices and data platforms

New York, NY9y exp
Oliver WymanNarayanamma Institute of Technology and Science

“Backend/data engineer from Oliver Wyman who built and ran production Python (FastAPI) services on AWS (ECS/Lambda/API Gateway) supporting risk modeling and regulatory reporting. Strong in reliability/observability, Glue-based ETL with data quality controls, and legacy SAS-to-Python modernization with rigorous parity validation; also demonstrated measurable SQL performance wins and cost-control improvements in serverless scaling. Based in Raleigh, NC and can travel onsite for important Bethesda-area meetings.”

AgileAmazon ECSAmazon EC2Amazon EKSAmazon RDSAmazon S3+150
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AP

Anurag Patil

Screened

Mid-level Data Analyst specializing in machine learning, ETL, and real-world evidence analytics

California, USA6y exp
AbbVieUC Irvine

“Developed and productionized an AI-driven "indication finding" system for AbbVie to identify additional diseases a drug could target, working closely with clinical research teams on cohort inclusion/exclusion criteria and disease rollups. Leveraged an LLM to map clinical inputs to ICD codes and built configuration-driven ML pipelines (Cloudera ML, YAML, scheduled jobs) with structured testing and evaluation for reliability.”

PythonSQLRMachine LearningDeep LearningNeural Networks+65
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KM

keerthana medaveni

Screened

Mid-Level AI/ML Software Engineer specializing in agentic LLM systems

Dallas, Texas6y exp
DatatronUniversity of West Florida

“Built and deployed a production LLM-powered multi-agent compliance copilot (life sciences/finance) using LangChain/LangGraph + RAG over vector databases, delivered via async FastAPI on Kubernetes. Emphasizes audit-ready, deterministic outputs with schema constraints and citations, plus rigorous evaluation/monitoring; reports 60%+ reduction in manual research time and successful production adoption.”

AgileAJAXAmazon DynamoDBAmazon S3AngularApache Hadoop+142
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JT

Jingyi Tian

Screened

Junior Machine Learning Engineer specializing in MLOps and LLM/RAG systems

Houston, TX2y exp
Daxwell, LLCColumbia University

“LLM/agentic workflow builder focused on productionizing document-processing systems. Redesigned pipelines with LangGraph + RAG, schema-aware validation, and eval/monitoring loops; known for fast incident diagnosis (restored accuracy from ~70% to >95% same day). Partners closely with sales and stakeholders to deliver tailored demos and drive adoption (reported +40%).”

PythonRSQLTableauXGBoostMachine Learning+65
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SL

Samantha Larkin

Screened

Mid-level Marketing & Sales Development Associate specializing in public sector SaaS/EdTech

New York, NY4y exp
EdSolutions ConsultingYale University

“Public-sector-focused consultant with hands-on ownership of outbound/ABM, lead gen, and GTM strategy for early-stage and pre-launch products (including edtech). Built multi-channel campaigns spanning SEO/web copy, email, conferences, and direct outreach to state/district leaders, and created an Airtable onboarding system that cut prospect research time by 33%.”

AsanaCanvaChatGPTClaudeContent StrategyCRM+92
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SM

Shravya M

Screened

Senior AI/ML Engineer specializing in NLP, LLMs, and MLOps

Texas, USA6y exp
CVS HealthUniversity of North Texas

“LLM/agent workflow engineer with healthcare experience (CVS/CBS Health) who built and deployed a production call-insights platform using Azure OpenAI + LangChain/LangGraph, including sentiment and compliance checks. Demonstrates deep HIPAA/PHI handling (tenant-contained processing, redaction, RBAC/encryption/audit logging) and production rigor (testing, eval sets, validation/retries, autoscaling) to scale to thousands of transcripts.”

A/B TestingAgileAnomaly DetectionApache AirflowAzure Data FactoryAzure Machine Learning+139
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BH

Benjamin Hudnut

Screened

Junior Live Events & Music Operations professional specializing in booking, touring, and community events

Los Angeles, CA4y exp
Live NationUCLA

“Founder/director of the music and event production company Tuned In, personally driving outbound BD to book underground LA talent and produce 25 events, including a major Lunar New Year collaboration with Alice Longyu Gao. Also ran multi-channel voter/community outreach for the Frankie Carrillo campaign (door knocking, 1,000+ SMS) and built automation tools (Apple widget; AI image-to-CSV workflow at Live Nation) to improve operational efficiency.”

Budget managementData cleaningLeadershipNegotiationRTableau+61
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NN

Neha Nadiminti

Screened

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

4y exp
WalgreensUniversity of North Texas

“Built and deployed a production Retrieval-Augmented Generation (RAG) platform in a healthcare setting to automate clinical documentation review and summarization, targeting near-real-time, explainable outputs. Emphasizes grounded generation to reduce hallucinations, latency optimizations (chunking/embedding reuse), and PHI-safe workflows with access controls, plus strong orchestration experience using Apache Airflow.”

A/B TestingAnomaly DetectionApache AirflowAudit LoggingAWSAWS Glue+153
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NG

Niteesh Ganipisetty

Screened

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

Grand Rapids, MI4y exp
IntuitGrand Valley State University

“Built an LLM-powered learning assistant (EduQuizPro/EduCrest Pro) that uses RAG over URLs and PDFs to generate quizzes, notes, and explanations for students/professors. Emphasizes production robustness—implemented dependency fallbacks (FAISS/Sentence Transformers/Gradio), CLI-safe mode, and NumPy-based indexing—along with a custom orchestration layer to keep multi-step AI workflows reliable.”

A/B TestingAgileApache HadoopApache HiveApache KafkaApache Spark+112
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SK

Sasi Katamneni

Screened

Mid-level Data Scientist / AI-ML Engineer specializing in Generative AI and LLM applications

Dallas, TX5y exp
Baylor Scott & WhiteUniversity of North Texas

“Built a production GenAI-powered analytics assistant to reduce reliance on data analysts by enabling natural-language Q&A over Databricks/Power BI dashboards, backed by vector search (Pinecone/Milvus) and a Neo4j knowledge graph, including multimodal support via OpenAI Vision. Demonstrates strong real-world LLM reliability engineering with strict RAG, LangGraph multi-step verification, and Guardrails/custom validators, plus broad orchestration and production monitoring experience (Airflow, ADF, Step Functions, Kubernetes, Prometheus/CloudWatch).”

A/B TestingAgileAjaxAmazon API GatewayAmazon BedrockAmazon CloudWatch+267
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MM

Madhu Moutam

Screened

Mid-level Supply Chain Analyst specializing in logistics optimization and planning analytics

USA (Remote)4y exp
MaerskConcordia University

“Supply chain/procurement professional (Maersk) who leads end-to-end freight sourcing initiatives using heavy analytics (SAP/SQL/Python/Excel) to drive measurable savings. Known for automating sourcing workflows (60% faster bid evaluation) and building Power BI dashboards to monitor contract compliance and supplier performance post-implementation.”

ForecastingPredictive ModelingInventory ManagementDashboard DevelopmentSprint PlanningRegulatory Compliance+109
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OD

Orin Davis

Screened

Executive HR & Talent Consultant specializing in culture, DEI, and hiring science

New York, NY16y exp
illuceoClaremont Graduate University

“Org/people advisor with 20+ years applying systems thinking and data-driven methods to high-stakes change—spanning DEI transformations at an international consulting firm, profitability turnarounds in eldercare via company-wide facilitation, and executive coaching. Also designs compensation benchmarks for novel roles at international tech companies, enabling successful global hiring and growth.”

RecruitingPerformance ManagementTeamworkData AnalysisData CleaningRegression Analysis+117
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SR

Santhosh Reddy

Screened

Mid-level AI/ML Engineer specializing in deep learning, NLP/LLMs, and MLOps

MA, USA6y exp
Flatiron HealthClark University

“Built and shipped a real-time oncology risk prediction system used by doctors during patient visits, trained on clinical data in AWS SageMaker and deployed via FastAPI with sub-second responses. Emphasizes clinician-trust features (SHAP explainability, validation checks) and HIPAA-compliant controls (encryption, RBAC, audit logging), plus Kubernetes-based production operations with autoscaling, monitoring, and drift/retraining workflows; collaborated closely with oncologists at Flatiron Health.”

PythonRSQLJavaC++Bash+123
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BK

Bharath kumar

Screened

Director-level AI & Data Science leader specializing in GenAI, LLMs, and MLOps

Draper, UT12y exp
ThorneBharathiar University

“ML/NLP engineer currently working in NYC on a system that connects complex unstructured data sources to deliver personalized insights, using embeddings + vector DB retrieval and a RAG architecture (LangChain, Pinecone/OpenSearch). Strong focus on production constraints—especially low-latency retrieval—using FAISS/ANN, PCA, index partitioning, and Redis caching, plus PEFT fine-tuning (LoRA/QLoRA) and KPI/SLA-driven promotion to production.”

A/B TestingAPI DevelopmentAPI TestingApache HadoopApache HiveApache Kafka+251
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OB

Omkar Bhope

Screened

Staff Full-Stack Engineer specializing in AI platforms and infrastructure automation

San Jose, CA5y exp
Etched AIUC San Diego

“Backend/full-stack engineer building complex internal platforms and customer-facing demos at the intersection of infrastructure and product. Shipped a no-code Product Lifecycle Manager for manufacturing (3 manufacturers, 1000+ evolving tests) using AWS S3/SQS ingestion and extensible Postgres (EAV+JSONB) with end-to-end traceability. Also built a FastAPI-based company data intelligence platform with Okta-secured RBAC and an LLM/MCP layer for ChatGPT-like analytics over enterprise data sources.”

PythonCC++TypeScriptJavaScriptSQL+159
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JP

Jincheng Pang

Screened

Principal Data Scientist specializing in healthcare analytics and medical imaging AI

Sudbury, MA11y exp
AccessHopeTufts University

“Developed an LLM-driven recommendation agent in Azure Databricks to triage oncology patients and trigger second-opinion case creation using medical claims and EHR data. Uses ICD-10/CPT/J-code features in prompts, embeddings + vector DB similarity, and a backtesting framework emphasizing recall to avoid missing clinically relevant cases while supporting business revenue.”

A/B testingAWSComputer visionData analysisData pipelinesDeep learning+84
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SB

Silpa Bhavani

Screened

Mid-level Full-Stack Java Developer specializing in cloud-native microservices

Oakland, CA5y exp
BlockLamar University

“Software engineer with strong compliance-domain experience who built a customer-facing compliance and reporting dashboard using React/TypeScript with Spring Boot microservices. Demonstrates mature production engineering practices—contract-first APIs, event-driven architecture (Kafka/RabbitMQ), caching (Redis), and robust CI/CD + observability (Prometheus/Grafana/ELK)—and also created a Python-based audit automation tool adopted into the standard release process.”

AgileAmazon CloudWatchAmazon DynamoDBAmazon EC2Amazon EKSAmazon RDS+139
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