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Vetted Tableau Professionals

Pre-screened and vetted.

TableauPythonSQLPower BIDockerAWS
TM

Thomas Mason

Screened

Executive Strategic Operations Leader specializing in business transformation and process optimization

Berkeley, California19y exp
Lawrence Berkeley National LaboratoryUC Berkeley

“Program/operations leader with Booz Allen Hamilton experience turning around a near-canceled Millennium Challenge Account Indonesia procurement-training contract by implementing train-the-trainer, mentorship, and KPI/dashboard-driven execution. Currently supports the CFO organization at Berkeley Lab, translating high-level strategy into people/process/technology/governance plans with an executive operating cadence.”

Operations ManagementCross-Functional LeadershipBudget ManagementData VisualizationProcess ImprovementStakeholder Management+70
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AR

Anvith Reddy Dodda

Screened

Mid-level AI Engineer specializing in GenAI, NLP, and MLOps

Remote, USA3y exp
PayPalUniversity of Central Missouri

“LLM/agentic-systems engineer with PayPal experience hardening an LLM-powered fraud support assistant from prototype to production, focusing on low-latency distributed architecture, rigorous evaluation/testing, and security/compliance. Comfortable in customer-facing and GTM contexts—runs technical demos/workshops, builds tailored pilots, and aligns sales/CS with engineering to close deals and drive adoption.”

PythonPySparkSQLNoSQLNumPyPandas+200
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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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MP

Malav Pandya

Screened

Senior Solutions Engineer specializing in Enterprise SaaS, MarTech integrations, and AI agents

Los Angeles, California9y exp
Triple WhaleUC Irvine

“At Triple Whale, partnered with product, engineering, and sales to bring enterprise LLM-based budget recommendation agents from impressive prototypes to trusted production workflows. Strong in prompt/input tuning, explainable structured outputs, and running tightly-scoped POCs with clear success criteria—plus hands-on technical demos and post-sale implementation to drive adoption.”

Prompt EngineeringData AnalyticsAutomationREST APIsAPI IntegrationAPI Testing+68
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CA

Chirayu Arya

Screened

Senior Marketing Manager specializing in GTM, product marketing, and growth for SaaS and consumer tech

Austin, TX4y exp
ENSO HOMESDuke University

“Growth-creative marketer/designer who owns end-to-end experimentation across web and paid social/search. Led Enso Home’s site redesign and creative refreshes that materially improved lead gen (28% leads, -22% CPA, higher ROAS) and directed SCALIS product/video assets that supported an email-driven pipeline impact of $1.47M.”

Market ResearchCross-Functional LeadershipA/B TestingSEOContent StrategyGoogle Ads+67
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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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TW

Timothy Wong

Screened

Mid-level Data Engineer specializing in experimentation, analytics, and AI-driven product experiences

4y exp
ZoomInfoUniversity of Texas at Austin

“Built production LLM automations using the Claude API, including a sales enablement workflow that summarizes playbooks and incorporates sales call metadata into strategic one-pagers. Experienced in orchestrating and scheduling data pipelines with SnapLogic, Airflow, and Databricks, and in scaling LLM API calls via parallel/batch processing. Also partnered with HR to deliver prompt-tuned, automated Slack messaging aligned to business tone and acceptance criteria.”

A/B TestingAWSBigQueryConfluenceCRMData Engineering+94
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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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KA

Kartikeya Anand

Screened

Mid-level Machine Learning Engineer specializing in NLP, LLMs, and multimodal modeling

Ann Arbor, USA3y exp
University of MichiganUniversity of Michigan

“Built and productionized a telecom-focused RAG assistant by LoRA fine-tuning LLaMA-2 and integrating LangChain+FAISS behind a FastAPI service, with dashboards and a human feedback UI for engineers. Demonstrated measurable impact (≈40% faster document lookup, +8–10% retrieval precision) and strong MLOps rigor via Airflow orchestration, CI/CD, and monitoring for drift and failures.”

Anomaly DetectionAWSBERTCI/CDCUDAC+++111
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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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AB

Advitha Bawgi

Screened

Junior Full-Stack Software Engineer specializing in cloud-native microservices

India1y exp
DAZNArizona State University

“Backend engineer with hands-on IoT and AI product work: built a decoupled Raspberry Pi + AWS IoT Core weather monitoring backend and a Dockerized FastAPI LLM service on AWS ECS using OpenAI/HuggingFace with an emerging RAG layer. Also delivered measurable performance gains at DAZN by redesigning event-driven/serverless ingestion (SNS, S3->Lambda->DynamoDB), cutting latency ~30% and boosting throughput ~25% while automating ~90% of manual sync work.”

API GatewayAWSAWS LambdaCI/CDCCSS+102
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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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ED

Emmett Ding

Screened

Senior Strategy & Operations professional specializing in climate tech commercialization and investing

New Brunswick, NJ8y exp
AvnosPenn State University

“Strategy consulting and business operations professional with climate-tech and climate VC experience (Avnos, Earth Foundry, Strategy&). Led cross-functional work to update a techno-economic analysis and produce a pilot proposal for direct air capture, contributing to a won engagement; also served as Chief of Staff to GPs, streamlining diligence, dealflow, CRM, and LP reporting to boost executive productivity.”

Business DevelopmentMarket ResearchProcess ImprovementPythonSQLCRM+95
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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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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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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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TK

Tejaswi Kothapalli

Screened

Mid-level AI/ML Engineer specializing in Generative AI, RAG, and Conversational AI

3y exp
AetnaIndiana Tech

“Built a production RAG-based GenAI copilot backend at Aetna using Python/FastAPI, GPT-4, LangChain, and Azure AI Search, deployed on AKS with Prometheus/Grafana observability. Owned the system end-to-end (ingestion through deployment) and improved peak-time reliability by addressing vector search and embedding bottlenecks with Redis caching, index optimization, and async processing, plus added anti-hallucination guardrails via retrieval confidence thresholds.”

AgileAmazon SageMakerApache SparkAWSAWS LambdaAzure DevOps+165
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ML

Maurice Lange

Screened

Executive Technology & Data Leader specializing in cloud platforms, AI/ML, and enterprise data

Tampa, FL35y exp
HigherEchelonRotterdam School of Management, Erasmus University

“Former PwC Director with hands-on early-stage venture experience (e.g., BridgeLights, a big-data analytics concept for early fintech) spanning concept creation, platform architecture, and go-to-market experimentation. Strong focus on building scalable, modular data platforms with rigorous governance/compliance (data lineage, quality controls) and supporting technical diligence in investor-aligned environments.”

LeadershipStrategic PlanningRisk ManagementProcess ImprovementProject ManagementCI/CD+139
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DB

Dharmik Bhingradiya

Screened

Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps on AWS

TX, USA5y exp
BlackRockTexas A&M University-Kingsville

“AI engineer who built a production RAG-based internal analyst tool at BlackRock, fine-tuning an LLM on proprietary financial data and adding four layers of guardrails (input/retrieval/generation/output) to improve grounding and reduce hallucinations. Implemented a LangChain-based multi-agent orchestration (7 major agents) deployed on AWS ECS, with reliability measured via internal human evaluation, LLM-as-judge, and RLHF/drift monitoring.”

PythonSQLRJavaC++Machine Learning+90
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MK

Mahima Korad

Screened

Mid-level Supply Chain Analyst specializing in planning, procurement, and distribution operations

Santa Clara, CA5y exp
HD SupplySan José State University

“Sourcing/procurement professional with Accenture experience supporting telecom infrastructure expansion, owning RFQs through delivery and managing 12+ vendors. Known for strong supplier performance management (scorecards, KPIs, corrective actions) delivering ~97% on-time material delivery while cutting expedited freight 13% and avoiding ~AUD 500K in delay costs; also brings supplier onboarding and capability/capacity assessment experience from Nestlé and Accenture.”

DashboardingRoot Cause AnalysisKanbanMicrosoft ExcelPower BISQL+82
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AS

Aayushi Singh

Screened

Intern AI/ML Engineer specializing in robotics and computer vision

Los Angeles, CA0y exp
BoltIOTUSC

“Worked on Sophia the humanoid robot, building production animation pipelines and enhancing human-robot interaction via perception and behavior orchestration. Experienced in stabilizing noisy perception-driven state transitions and designing smooth, user-centered behavioral flows, collaborating closely with artists, animators, and experience designers to translate creative intent into measurable system behavior.”

AgileAngularJSBlenderBootstrapC++CI/CD+144
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