Vetted Tableau Professionals

Jurien Garrison

Screened

Principal Talent Acquisition Leader specializing in technical and GTM hiring for SaaS and AI

New York City, NY12y exp

“Recruiting leader managing teams of up to 26 who stays hands-on with high-impact executive searches; recently led and closed a VP of Revenue search in 60 days to unblock revenue growth. Partners closely with HRBPs and executive stakeholders (including CFO) on workforce planning, attrition reduction, and compensation/leveling decisions, and has rebuilt recruiting processes with structured, metrics-driven adoption.”

Somil Shah

Screened

Mid-level AI/ML Engineer specializing in generative AI, RAG platforms, and LLM agents

San Francisco, CA4y exp

“AI/LLM engineer who has shipped 10+ production applications, including InvestIQ on GCP—a production-grade RAG due-diligence engine that ethically scrapes web/PDF sources, builds a ChromaDB knowledge base, and delivers analyst-style dashboards plus a citation-backed chat copilot. Deep focus on reliability (evidence-only answers, hard citations, refusal gating), retrieval tuning, and orchestration (Airflow/Cloud Composer), plus multi-agent systems (CrewAI with 7 specialized finance agents).”

Akam Pachachi

Screened

Executive Sales & Partnerships Leader specializing in Enterprise SaaS, Travel Tech, and Market Expansion

Oshawa, Canada14y exp

“Partnerships and growth leader (Traveronto) specializing in partner-led GTM through enterprise/API integrations and white-label distribution. Uses rigorous analytics (audience overlap, engagement quality, cohort retention/LTV) to source and scale creator/platform partnerships, and runs funnel-driven A/B tests on onboarding and pricing to improve activation, GMV, and recurring revenue while keeping CAC low.”

Mohithkumar Bolisetti

Screened

Mid-level Java Full-Stack Developer specializing in microservices and cloud platforms

Strongsville, Ohio5y exp

“Full-stack engineer focused on modernizing legacy financial/compliance platforms into cloud-native, domain-driven microservices. Deep hands-on experience across Spring Boot/Kafka/Redis/Postgres-Mongo backends and React/Angular frontends, with strong CI/CD and Kubernetes/OpenShift deployment practices for real-time, high-volume workloads.”

Archana yaramala

Screened

Mid-level AI/ML Engineer specializing in deep learning, MLOps, and LLM applications

NY, USA4y exp

“Built and deployed production LLM assistants for internal Q&A and customer-feedback summarization, emphasizing reliability (RAG, prompt tuning, validation/whitelisting) and privacy safeguards. Improved adoption by adding explainable outputs and a user feedback mechanism, and has hands-on orchestration experience with Aflow and Azure Logic Apps.”

Bala Venkateswarlu K

Screened

Mid-level Data Scientist specializing in Generative AI, NLP, and MLOps

USA5y exp

“Built and deployed an LLM-powered claims-document summarization system (insurance domain) that cut agent review time from 4–5 minutes to under 2 minutes and saved 1,200+ hours per quarter. Hands-on across orchestration and production infrastructure (Airflow retraining DAGs, Kubernetes, SageMaker endpoints, FastAPI) and recent RAG workflows using n8n + Pinecone, with a strong focus on reliability, cost, and explainability for non-technical stakeholders.”

“Data engineer focused on marketing/web analytics and external API pipelines, handling ~10M records/week. Built Azure-based ingestion and PySpark transformations with rigorous data quality checks, then served curated datasets into Synapse/Redshift for Power BI. Also designed an Airflow-orchestrated crypto REST API pipeline with monitoring, retries/exponential backoff, schema-change detection, and backfill-friendly reprocessing.”

“Analytics-focused candidate with internship and project experience at Recotap and CoUnderscore, combining SQL, Python, and BI dashboards to turn messy marketing and engagement data into decision-ready reporting. Stands out for tying analytics work to business outcomes, including ~15% CTR improvement, identifying ~40% misattributed spend, and enabling a ~$75K budget shift through better targeting.”

“Analytics professional with Northern Trust experience focused on investment portfolio reconciliation and reporting. They combine SQL, Python, and Power BI to clean and validate high-volume financial data, automate manual processes, and align operations and accounting teams on shared metrics—driving roughly 20% improvement in reconciliation accuracy.”

“Analytics professional at Optum with hands-on experience turning messy healthcare claims data from SQL, Excel, and CRM systems into validated reporting datasets and Power BI dashboards. They also built reproducible Python workflows for claims analysis and owned an end-to-end project focused on improving claims processing efficiency through metric design, segmentation, and stakeholder-driven operational improvements.”

“Analytics professional with hands-on experience unifying marketing-platform data through Fivetran and Snowflake, building reporting views, and catching source-to-report issues like timezone-driven spend discrepancies. They also owned subscription LTV/cohort analysis and engagement tracking initiatives, partnering with e-commerce, product, and senior leadership to turn behavioral and demographic data into dashboards, lead-qualification metrics, and lifecycle marketing insights.”

“Analytics professional from Capital One with strong experience automating risk, reconciliation, and regulatory reporting workflows in financial services. They combine deep SQL/Python pipeline skills with stakeholder-facing dashboard and KPI design, delivering measurable impact like 30% performance gains, sub-24-hour anomaly detection, and 100% data integrity for regulatory filings.”

“Analytics professional with hands-on experience in supply chain and logistics transformation, including enterprise data preparation in SQL, Python automation, and Power BI reporting. They highlight ownership of end-to-end digitization work at Blue Dart, where they defined operational metrics, aligned cross-functional stakeholders, and delivered measurable gains in transparency, reporting efficiency, and implementation quality.”

“GenAI/ML engineer with hands-on experience building production financial intelligence and document summarization systems at Citibank. Stands out for combining LLM fine-tuning, hybrid RAG, multi-agent workflows, and strong MLOps/observability practices to deliver measurable business impact, including 60% faster analyst retrieval, 31% higher precision, and 99%+ uptime.”

Sarfaraz Karim

Screened

Mid-level Finance Analyst specializing in product, analytics, and technology strategy

Chicago, IL4y exp

“Startup-oriented business development candidate who built outreach and pipeline processes from scratch for early-stage companies including a law firm and consulting-related work. Stands out for highly persistent, research-driven prospecting across social, email, phone, and even in-person outreach, including winning a hotel client after failed remote attempts by showing up with a tailored strategy.”

“Analytics candidate with strong finance/operations reporting experience, focused on billing, margin, and revenue leakage use cases. They have built SQL and Python workflows that turned messy shipment, invoice, PO, and ERP data into trusted reporting layers, replacing manual Excel processes and driving adoption through transparent reconciliation and stakeholder collaboration.”

“Developer in the mortgage domain who owns regulated client-letter and reporting changes across front-end scripting, serverless testing environments, and SQL/reporting workflows. They stand out for improving release operations by introducing SOAP UI testing, which nearly doubled letter-update throughput even while serving as the only developer on these projects, and for quickly resolving production issues within 24 hours.”

“Frontend developer who helped drive a high-stakes migration from a legacy CMS-rendered UI to a code-based implementation in Visual Studio Code, acting as a POC for asset tracking and rollout coordination. They emphasize hands-on testing, QA collaboration, reusable JavaScript UI work, and cross-browser fixes, and cite a successful production launch that received positive customer feedback and internal appreciation.”

Briana Lonappan

Screened

Entry-level product and project management candidate specializing in operations and user insights

Remote2y exp

“Early-career candidate with a blend of product research and project coordination experience from a BeReal Product Innovation Externship and Aspire Skill Development internship. They bring strong analytical and organizational skills, including user interviews, competitive benchmarking, prototyping, and stakeholder tracking, with a demonstrated contribution to reducing missed deadlines by 20%.”

“Backend-leaning full-stack engineer who has shipped both a SaaS analytics/A-B testing platform and an AI-driven fraud monitoring product in production. Stands out for combining React/TypeScript frontend work with Python/Java backend systems, event-driven architecture, and practical LLM integration grounded by validation and human analyst feedback, with measurable impact on engagement, performance, fraud accuracy, and false positives.”

Jalaan Fields

Screened

Mid-level finance and strategy analyst specializing in valuation and performance analytics

Remote7y exp

“Co-founder of ATW Labs who built a consulting and analytics pipeline from scratch, selling into middle-market companies and converting outreach into repeat client engagements. Brings a blend of founder empathy, executive-facing business development, and early conviction around practical generative AI use cases, with experience translating ambiguous client needs into high-ROI recommendations.”

“Senior Business Strategist (Robotproof) who effectively operated in a Chief-of-Staff-like capacity for both internal executives and Samsung’s President/CMO/Head of Strategy, running multi-workstream initiatives across strategy, marketing, and VR product/engineering. Built KPI/OKR dashboards and executive briefing rhythms to accelerate decisions and delivered an 8% sales lift via a targeted regional strategy pilot that included localized assets, an incentivized sales program, and a bespoke VR training tool.”

“AI/LLM engineer who built a production intelligent support system using RAG over a vectorized documentation library, addressing real-world issues like lost-in-the-middle context failures and doc freshness via automated GitHub-driven re-embedding pipelines. Emphasizes rigorous agent evaluation (component/E2E/ops) and prefers lightweight, decoupled workflow automation using message brokers (Redis/RabbitMQ) over heavyweight orchestration frameworks.”

“Healthcare-focused LLM engineer who deployed a production triage and clinical knowledge retrieval assistant using RAG and LangGraph-orchestrated multi-agent workflows. Emphasizes clinical safety and compliance with robust hallucination controls, HIPAA/PHI protections (tokenization, encryption, audit logging, zero-retention), and human-in-the-loop escalation; reports a 75% latency reduction in a healthcare agent system.”