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Vetted Tableau Professionals

Pre-screened and vetted.

NM

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

4y exp
New York Life
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CP

Director-level Paid Social & Search Strategist specializing in entertainment and e-commerce growth

15y exp
Mango Films
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FK

Senior Java Full-Stack Developer specializing in cloud-native microservices and FinTech

Bristow, VA9y exp
Bank of America
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AB

Executive Engineering Leader specializing in data platforms and SaaS

Los Angeles, CA13y exp
Los Angeles County Office of Education
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PS

Senior Customer Success Manager specializing in Enterprise SaaS retention and AI enablement

San Francisco Bay Area, CA11y exp
Builder.ai
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GD

Senior Data Engineer specializing in cloud data platforms and real-time streaming pipelines

Rosemont, IL11y exp
Wintrust
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AM

Mid-level Backend Software Engineer specializing in data platforms and reporting

Pleasanton, CA5y exp
Workday
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TS

Senior Data Engineer specializing in multi-cloud data platforms and real-time analytics

Sunny Isles Beach, FL10y exp
Capgemini
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AM

Senior Data Scientist specializing in healthcare analytics and scalable ML pipelines

Philadelphia, PA11y exp
CoverMyMeds
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CF

Christina Flores

Screened ReferencesStrong rec.

Director-level Executive Operations & Administrative Leader in government, nonprofit, and private office settings

New York, NY14y exp
HillspireCalifornia State University, Channel Islands

Executive operations/project leader who managed cross-entity priority initiatives for Eric Schmidt’s family office, driving alignment through structured reporting and dashboards. Led a board-level digital transformation at ACC, moving a 14-member Board of Trustees from paper processes to board software, and brings high-discretion experience supporting Senator Warner.

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VD

Vaishnavi Dangety

Screened ReferencesStrong rec.

Senior Talent Acquisition Operations leader specializing in scalable global recruiting programs

Dallas, TX13y exp
FeujiUniversity of Mumbai

Recruiting Operations leader who has managed 6–12 person teams and owned the full recruiting ops lifecycle, including ATS governance, reporting, capacity planning, and vendor coordination. Notably redesigned interview scheduling/feedback workflows to cut time-to-fill 25–30% for priority technical roles, reduce candidate drop-off ~20%, and boost recruiter load capacity 15–20% without sacrificing quality; also led an end-to-end CPAL ATS implementation reducing manual scheduling effort by ~40%.

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SY

Mid-level Cybersecurity Analyst specializing in SIEM, incident response, and Zero Trust

Remote, USA3y exp
BigCommerceYeshiva University

Cybersecurity/SOC-focused engineer with hands-on production experience integrating and tuning Splunk Enterprise Security for a zero-trust program, including CIM normalization, correlation/risk-based detection tuning, and performance optimization via forwarder-level filtering and index strategy. Has cross-disciplinary incident troubleshooting experience spanning SIEM, networking, and hardware, and has automated customer/team-specific security workflows using Python in Splunk playbooks; collaborated on-site with HSBC IT/SOC teams to deliver dashboards and security policies.

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MS

Senior Machine Learning Engineer specializing in MLOps and Generative AI

St. Louis, Missouri7y exp
Emerson
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PK

Senior Data Engineer specializing in multi-cloud data platforms and generative AI

Weston, FL5y exp
UKGUniversity of Alabama at Birmingham
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TL

Senior Software Engineer specializing in ML/AI and scalable data platforms

San Jose, CA11y exp
LabelboxNational University of Singapore
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RR

Mid-level Data Scientist specializing in financial ML, NLP, and MLOps

San Diego, CA5y exp
Morgan StanleySan Diego State University
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LD

Lew Donley

Screened ReferencesStrong rec.

Senior Creative Design & Innovation Leader specializing in brand strategy and human-centered design

Normal, IL18y exp
TriMasIllinois State University

Creative director/designer spanning high-polish marketing brand work and enterprise innovation: built a full podcast brand ecosystem and a cinematic historical visualization using Google Veo 3. Also led an AR/VR-assisted remote troubleshooting initiative at TriMas (HoloLens-style workflows), delivering a 40% MTTR reduction and cutting expert travel by 50%+ while standardizing reusable interaction components for global teams.

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VV

Vaishnavi Veerkumar

Screened ReferencesStrong rec.

Mid-level AI Engineer specializing in GenAI and RAG systems

Boston, MA4y exp
VizitNortheastern University

AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.

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JG

Jan Gavile

Screened ReferencesStrong rec.

Senior Digital Marketing Manager specializing in paid media and growth marketing

Remote10y exp
LabcorpDe La Salle University

Performance marketer managing a $500K/month paid media portfolio across Google, Microsoft, Meta, TikTok, Reddit, YouTube, and Quora with a focus on profitable growth. Uses a rigorous testing framework across creatives, bidding, and landing pages (leveraging Adobe Analytics and customer journey dashboards) and cites 200–400% YoY revenue growth plus 200–300% ROAS improvement; recently restored 20–30% of lost conversions at Labcorp within two weeks after diagnosing competitive and seasonal shifts.

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RD

Rachel Downey

Screened ReferencesStrong rec.

Mid-Level Game Designer specializing in systems and economy design

Livermore, California4y exp
ScopelyFull Sail University

Game economy/progression designer with hands-on ownership of end-to-end systems and live-ops tuning on major mobile titles (Star Trek Fleet Command, Marvel Contest of Champions). Builds spreadsheet-based simulations and telemetry-driven tuning loops to prevent inflation and reduce progression friction, including a multi-iteration optimization that lifted D7 retention ~7% while maintaining monetization targets.

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IP

Ivan Pavkovic

Screened

Senior Paid Ads Specialist specializing in multi-platform performance marketing

Remote9y exp
KPMGUniversity of Zagreb

Performance marketer focused on e-commerce growth, managing $120K/month in spend across Google and Meta with reported 5x+ ROAS. Emphasizes full-funnel structure and creative iteration (copy, hooks, UGC) in collaboration with in-house creative teams, and prioritizes client reporting around sales/profit outcomes.

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AD

Akshay Danthi

Screened

Senior AI Engineer specializing in production GenAI systems

San Francisco, CA8y exp
MajorlyGolden Gate University

AI engineer who has shipped production LLM systems end-to-end, including a natural-language-to-SQL analytics copilot for career advisors that achieved ~95% query success through schema grounding, access controls, and automated regression testing with golden queries. Also builds LangGraph-orchestrated multi-step agents (resume analysis, recommendations) and RAG pipelines (PDF ingestion + FAISS) and partners closely with non-technical users to drive adoption and trust.

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SP

Soham Patel

Screened

Mid-level Machine Learning Engineer specializing in healthcare NLP and MLOps

Piscataway, NJ3y exp
Syneos HealthRutgers University - New Brunswick

ML/AI practitioner in healthcare (Syneos Health) who has deployed production clinical NLP and risk models. Built a BERT-based physician-note information extraction system on Docker + AWS SageMaker (reported ~42% retrieval improvement) and automated retraining/deployment with Airflow and drift detection, while partnering closely with clinicians to drive adoption (reported ~18% readmission reduction).

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ST

Mid-level AI/ML Engineer specializing in GenAI and predictive modeling

Fullerton, California5y exp
UnitedHealth GroupGeorge Washington University

Built and deployed a GPT-4-powered medical assistant for clinical staff to reduce time spent searching guidelines and EHR information, with a strong emphasis on safety and compliance. Uses strict RAG, confidence thresholds, and fallback behaviors to prevent hallucinations, and runs production-grade workflows orchestrated with LangChain/LangGraph plus Docker/Kubernetes/MLflow and monitoring for reliability and cost.

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