Vetted A/B Testing Professionals

“Growth/partnership marketer who led Bird Heating & Cooling’s post-rebrand go-to-market and built trackable acquisition loops across Google Search, landing pages, email, and retargeting. Strong at converting local events/sponsorships into measurable leads using QR codes, UTMs, call tracking, and tight lead-routing workflows, and scaling repeatable partnership frameworks.”

“Full-stack engineer from Vagaro who owned an end-to-end rebuild of a sluggish WordPress sales site into a Next.js 15 app hosted on Azure, adding Hygraph headless CMS, SSR, i18n, and a reusable component library. Instrumented Amplitude + A/B testing/heatmaps and reports a 10% sales lift post-launch; also has AWS ops experience (S3/IAM/CloudWatch) and has built ingestion pipelines including LLM-powered unstructured data processing with dead-letter handling.”

“Product/UX designer with experience building an end-to-end AI campaign/session platform that converted an engineer-led, code-heavy workflow into a self-serve marketer product using a target/act/schedule interaction model, progressive disclosure, and real-time previews. Also redesigned monitoring for Informatica’s enterprise data platform after field research with data engineers, shifting the UI toward lifecycle views and failure-state observability.”

“Robotics software engineer with deep ROS2 experience who built a modular autonomous robotics stack (perception/sensor fusion, localization+mapping, and planning). Led development of a LiDAR+camera fusion and multi-object tracking pipeline (PCL + YOLO + Kalman filtering) and debugged real-time SLAM/localization issues via QoS/timestamp synchronization, EKF tuning, and SLAM Toolbox parameter optimization using Gazebo/RViz and rosbag replay.”

“Senior Account Manager with hands-on ownership of a $50K/month CPG paid media program spanning OTT/CTV, programmatic display, SEM, Meta (and TikTok), combining rigorous test design with cross-functional execution (media planning + ad ops + channel teams). Delivered concrete gains including 25–30% lift in FTA and a 15% reduction in CTV CPM, leading to increased client budgets and an upsell into audio.”

“Paid media performance marketer with hands-on ownership of a $100K/month higher-education account spanning LinkedIn, Google Ads, and programmatic display/video. Built a structured 6-week experimentation approach (2-week test intervals) and used geo-fencing to reach military audiences, exceeding attendance goals for online MBA informational sessions (avg ~45 attendees vs 30 target). Strong in diagnosing stalled performance and translating complex metrics into client-friendly insights.”

“Built and deployed an LLM-powered mental health therapy assistant at AppHealth that segments users by stress level and delivers personalized, non-medical guidance. Implemented healthcare-focused safety guardrails (secondary LLM output filtering) and a multi-agent router workflow validated via statistical tests and therapist review, then scaled training/inference on AWS (EC2/Lambda/DynamoDB) with Kubernetes.”

“Growth/brand leader who drives measurable revenue outcomes through rebrands, GTM execution, and multi-channel acquisition. Has delivered on-time/on-budget website + brand rebuilds via sourced expert partners, improved conversion from 3% to 8% for an MSP using outsourced outbound, and helped an industrial manufacturer exceed a $2M revenue goal by reaching $3M through repositioning and market expansion.”

“Cloud/ML engineer with production deployment experience on Azure (Dockerized models, managed APIs, data pipelines) who has repeatedly stabilized unreliable systems—e.g., taking an API-driven analytics pipeline from ~60% to 98% reliability and an Azure ML service from ~80% to 97% by addressing rate limits, container memory, and gateway timeouts. Also built an explainable contract-risk model for entertainment bookings (Transformers + SHAP) and integrated it into a legacy booking system via a Flask REST API, plus prior IoT work at Nissan processing CAN bus sensor streams for diagnostics/anomaly insights.”

“Built and deployed a production LLM-powered support assistant for customer support agents using a RAG architecture over internal docs and past tickets, with human-in-the-loop review. Demonstrates strong applied LLM engineering focused on real-world constraints (hallucinations, latency, cost) using routing to smaller models, reranking, caching, and rigorous evaluation/monitoring (offline eval sets, A/B tests, KPI tracking).”

“Growth/partnerships operator in the creator ecosystem who runs creator-led GTM launches and brand collaborations (not yet a traditional gaming studio partnership). Has executed a baby wellness program launch using Facebook/TikTok/Instagram plus live Zoom Q&As and co-branded partnerships, and designed outcome-based email re-engagement loops to improve repeat engagement; helped drive a campaign that led to a SEA creator award.”

“Built and deployed a real-time hospital readmission risk prediction system at NYU Langone Health, combining structured EHR data with BERT-based NLP on clinical notes and serving predictions to clinicians via Azure ML and FHIR APIs. Emphasizes production reliability and clinical trust through SHAP-based explainability and robust healthcare data preprocessing, and reports a 22% reduction in 30-day readmissions.”

“Full-stack developer with Manulife experience building and scaling a customer-facing digital wealth portfolio tracker and a complex React/TypeScript portfolio dashboard. Strong track record improving mobile UX and reliability with measurable impact (30% lower mobile bounce rate; ~20–22% fewer Stripe payment errors) through CI/CD automation, A/B testing, and monitored incremental rollouts.”

“ML engineer/data scientist who built and deployed a real-time fraud detection platform at Citi on AWS SageMaker, processing 3M+ daily transactions and improving fraud response by 28%. Combines unsupervised anomaly detection (autoencoders) with ensemble models (XGBoost/Random Forest) plus Airflow/Step Functions orchestration, drift monitoring, and explainability (SHAP) to keep models reliable and compliant in production.”