Vetted Data Analysis Professionals

JiHeon Kim

Screened

Mid-Level Backend Software Engineer specializing in Financial Services

Toronto, Canada4y exp

“Frontend engineer focused on React/TypeScript dashboards and end-to-end product delivery, including RBAC with JWT, Redux-based session persistence, and a centralized API layer with token injection. Has experience with real-time MongoDB-backed updates (shared across web and mobile) and has solved production-impacting issues like timezone inconsistencies using date-fns/UTC conversions, backed by Jest + manual QA and rollback-driven release practices.”

“QA leader with end-to-end ownership of a web-UI automated B2B pricing platform at Cargill, known for using defect trend analytics (Jira/Jira AI) to uncover systemic config/integration risks before UAT/production. Implemented durable CAPA controls (config-change impact assessment gates) and improved release transparency with Copilot-generated Confluence readiness dashboards; cites 15% logistics cost reduction and 60% operational efficacy improvement. Also coordinated cross-shore QA teams across multiple countries with structured cadences and escalation paths.”

“Wealth management sales professional who built a book of business through high-volume cold calling and relationship-driven networking, converting personal-network introductions into paying clients. Applies a VC-style lens to founder sourcing and early evaluation (problem, traction signals, founder insight), with an emphasis on disciplined CRM-based pipeline management.”

Jaskirat Singh

Screened

Mid-level Software Engineer specializing in cloud infrastructure and data platforms

Eden Prairie, MN5y exp

“Infrastructure/data platform engineer with hands-on GCP production experience, especially Bigtable, who led a migration from Azure Cosmos DB Cassandra API to Bigtable that removed throttling and cut costs by 50%+. Stands out for combining distributed data architecture, zero-downtime Kafka migration strategy, and Terraform/Python automation for deterministic multi-region GKE operations.”

“Marketing analytics candidate with experience at WPP and on a global Coca-Cola campaign, focused on turning messy multi-platform media data into trusted reporting and decision systems. They combine hands-on SQL/Python pipeline building with stakeholder KPI alignment, and cite a 22% improvement in media effectiveness plus faster budget reallocation through daily automated reporting.”

“Analytics professional with higher education experience at the University of Dayton, focused on turning inconsistent operational data into standardized metrics and recurring dashboards. They combine SQL, Python, and Power BI to automate reporting, improve data integrity, and reduce manual reporting by 30%, with outputs adopted in semester planning and cross-department performance tracking.”

Kaitlyn Silver

Screened

Junior HR analytics and business student specializing in people data and strategy

Atlanta, GA3y exp

“Early-career candidate and current college senior who serves as a TA for an entrepreneurship class, where they teach structured outbound sales methods. While they lack direct sales-role experience, they demonstrate unusually strong conceptual knowledge of cold calling, stakeholder mapping, qualification, and data-driven messaging optimization, plus hands-on performance marketing experience from running a social media account.”

“CRM and retention marketer with 4+ years of experience across leading Indian consumer and D2C brands including My11Circle, Nykaa, and Croma. Brings hands-on multi-channel lifecycle expertise across email, WhatsApp, SMS, RCS, and in-app, with end-to-end ownership of promotional and retention journeys and a cited 28% lift in repeat purchases from a replenishment campaign.”

John Patton

Screened

Executive Atlassian and Agile transformation leader specializing in AI-enabled enterprise collaboration

Aberdeen, NJ6y exp

“Product leader with hands-on experience modernizing enterprise internal tooling and shipping AI-enabled support workflows. At Peloton, they led the end-to-end migration of Jira, Confluence, and JSM from on-prem Data Center to cloud; at Atlas Vega, they implemented a RAG-based Slack/JSM support assistant with strong governance, data hygiene, and measurable support outcomes.”

“Frontend-focused candidate with hands-on experience building React and TypeScript dashboards for searching, filtering, and analyzing large datasets in real time. Demonstrates practical performance tuning skills using React DevTools, memoization, debouncing, and pagination, and has also built a Mapbox-based location data dashboard with interactive markers and popups.”

“Product leader with strong experience in highly regulated benefits and claims environments, including building statutory benefits systems and launching AI-enabled claims automation. Stands out for navigating regulatory ambiguity, legacy/API integration, and executive alignment while still shipping on time and under budget, with a clear philosophy that AI should augment human work rather than replace it.”

Murali Marupudi

Screened

Mid-level Backend Engineer specializing in Python microservices and scalable cloud systems

Jersey City, NJ4y exp

“Backend engineer focused on high-throughput Python/Flask systems on AWS, with strong scaling and performance tuning experience (e.g., PostgreSQL join reduced from ~3s to <200ms; background aggregation cut from 10 minutes to <90 seconds with 8x throughput). Has also integrated ML model serving into production APIs (churn prediction) using Celery/Redis batching and AWS Lambda/S3, and designed secure multi-tenant architectures with PostgreSQL schema isolation and row-level security.”

“Product leader in education and assessment who led a major TOEFL iBT transformation, combining global stakeholder alignment, adaptive testing, and human-in-the-loop AI scoring/content systems. Also brings large-scale people leadership experience, having managed a 1,300-instructor cybersecurity training operation while launching adjacent programs in digital marketing, AI, and software development.”

“Startup operator and co-founder who helped build SmartSquash AI from pre-product, pre-revenue stage to $600K ARR in 2 months, 125+ club pilots, a PSA enterprise analytics partnership, and a $1.4M acquisition. Brings a rare mix of 0-to-1 product/GTM execution and trust-sensitive AI deployment, plus process improvement experience at Microsoft that drove major efficiency and cost savings.”

“Montreal-based MBA (Queen’s University) with experience in sports/creator talent representation and growth marketing. Sourced athlete creators through research and LinkedIn outreach, helping facilitate signings and tracking success via social analytics and campaign performance. Also worked as a pricing analyst in the secondary sports ticket market, using historical data to optimize purchasing toward high-return games.”

“AI engineer who has shipped production LLM systems across customer service and marketing use cases—building a RAG app on Azure OpenAI and speeding retrieval with Redis caching tied to Okta sessions. Also implemented a LangGraph multi-agent workflow that pulls image context from Figma to generate structured HTML marketing emails, adding a verification agent to improve image-selection accuracy while optimizing solution cost for business stakeholders.”

“Robotics/ROS2-focused early-career engineer who built a stereo visual-odometry SLAM system for autonomous navigation and optimized it to run reliably in real time on Raspberry Pi. Strong in sensor fusion (camera+IMU), ROS2 debugging/profiling, and distributed robotics/IoT pipelines (ROS2 + MQTT + cloud), with added experience extracting WiFi CSI for sensing/localization and shipping via Docker + GitHub Actions CI/CD.”

“Built a web-based online Sudoku game in JavaScript (multiplayer format supporting up to 6 teams with up to 5 players each) and demonstrates strong product/analytics orientation. Uses a KPI-driven approach (DAU/WAU, ARPU, session duration, LTV) and structured prioritization methods (MoSCoW, story mapping, cost of delay, DFV) to iterate toward targets; seeking a remote role around $70k/year.”

“Built a production, agentic multi-agent pharmaceutical intelligence system for US oncology (breast cancer) conference/news intelligence, automating MSL-style information gathering and summarization for pharma and healthcare stakeholders. Uses CrewAI + LangChain orchestration, custom scraping across ~15 pharma newsrooms, and a grounding-score evaluation approach (sentence transformers/cosine similarity) to mitigate hallucinations.”

“ML practitioner with hands-on experience in healthcare time-series modeling (CGM-based blood glucose prediction) including a novel ICA-based blind source separation approach and robust data-cleaning for noisy, missing sensor data. Also built an embeddings + LLM-powered podcast recommendation workflow using YouTube transcript scraping and Vellum AI document indexing, with a strong emphasis on production-grade engineering practices (TDD, monitoring) and realistic rolling validation for forecasting.”

“ML/LLM engineer at Charles Schwab who built a production loan-advisor chatbot integrated with internal knowledge and loan-calculator APIs, adding strict numeric validation to prevent rate hallucinations and optimizing context to control costs. Also runs ~40 Airflow DAGs orchestrating retraining/ETL/drift monitoring with an automated Snowflake→SageMaker→auto-deploy pipeline, and uses rigorous testing plus canary rollouts tied to business metrics and compliance constraints.”

“Enterprise healthcare GTM/CS leader who owned large accounts end-to-end (sales through renewal), including scaling a hospital network rollout to 51 of 52 facilities in ~3 months. Built an automated customer-feedback and response system (“Schism”) using n8n + ChatGPT that cut CS workload by ~50% and informed product priorities, and has experience driving cross-functional EHR-related deployments and GTM analytics (Metabase/Snowflake/Firebase).”

“Built and shipped a production LLM-powered agent that automated purchasing and inventory operations by integrating with live ERP data and returning structured, machine-readable outputs usable by downstream systems. Emphasizes real-world reliability through orchestration, strict schemas/validation, confidence-based fallbacks with human handoff, and monitoring/evaluation feedback loops to reduce silent failures and make issues observable.”

Ann-Marie Waterman

Screened

Executive Higher Education Administrator specializing in operations, finance, and enrollment management

Baltimore, MD29y exp

“Higher-education operations leader (Assistant Dean at Howard University School of Business; inaugural Associate VP of Student Affairs/Enrollment Management at University of the District of Columbia) known for rebuilding and modernizing internal operations under constraint. Delivered measurable results including sustaining fiscal integrity across three budget cycles post-staff reduction and improving admissions throughput (+25% applications, 50% faster decisions) through process re-engineering, automation, and cross-functional governance.”