Vetted Financial Modeling Professionals

“Built and deployed a production LLM-assisted recommendation and insights platform that unifies structured, semi-structured, and unstructured data via a modular ingestion pipeline, canonical schemas, embeddings, and late-fusion modeling. Experienced in operationalizing ML/LLM systems with Airflow and Kubernetes (Dockerized services, autoscaling, rolling updates) and emphasizes reliability through layered testing, guardrails, monitoring, and A/B experimentation while partnering closely with non-technical stakeholders.”

“Longtime entrepreneur building an augmented/virtual reality company with MVPs already in production; raised just under $100K over the past year via SAFE notes. Uses market and competitive analysis (including Meta/Apple ecosystem moves) and partner-driven go-to-market planning, and is currently focused on validating content and completing development with additional technical collaborators.”

“Data-driven growth and partnerships professional with experience leading an analytics/reporting vendor rollout end-to-end (vendor selection via stakeholder interviews and PoC, then negotiating scope/pricing/support and tracking adoption/efficiency/accuracy KPIs). At PC Financial, built regression and segmentation models to optimize multi-channel targeting (in-app/email/push), driving +15% campaign engagement and +10% PC Optimum offer loads, and ran behavior-triggered lifecycle experiments that lifted upsell conversion by 20%.”

Reenam Jot Kaur

Screened

Junior Business Operations & Systems Analyst specializing in automation, QA, and analytics

San Francisco, CA3y exp

“Operational/data-focused QA professional who applies manufacturing-style quality gates to supplier workflows, owning supplier data quality from onboarding through billing readiness. Built automated validation and variance-threshold checks (Tableau/Excel-driven monitoring) and partnered directly with suppliers to resolve pricing discrepancies early, preventing large-scale transaction and billing issues.”

“VC/IBD candidate with experience at boutique firm True Blue Partner, focused on sourcing and evaluating early-stage companies in areas like AI and logistics. Brings a structured, high-volume founder sourcing approach, personalized outbound strategy, and strong early-signal judgment to move cold leads into active investment discussions.”

Li Pan

Screened

Junior Investment Banking / Hedge Fund Analyst specializing in equity research and valuation

Austin, TX2y exp

“Early-stage investor/operator profile with experience at AugCap sourcing and evaluating founder-led opportunities via high-volume outbound (email/LinkedIn) and turning cold outreach into partnership discussions, including supporting valuation and strategy work. Also built Carquote.AI and drove early traction by landing 20+ paying pilot users in four weeks.”

Alexander Home

Screened

Mid-level investment analyst specializing in portfolio analysis and financial modeling

Oregon, USA4y exp

“Sales-focused candidate with high-volume outbound experience targeting founders and operators, primarily through LinkedIn, email, and cold calling. They report operating at 200 calls per day, booking 10 meetings per week, and contributing to $5M per quarter, with a founder-sourced opportunity specifically cited as bringing in $5M of business. They emphasize tailored messaging, trust-based relationship building, and disciplined CRM pipeline management in fast-paced environments.”

Ramnik Sekhon

Screened

Mid-level Customer Success & Implementation Strategist specializing in B2B SaaS onboarding

San Francisco, CA8y exp

“B2B SaaS Customer Success Manager based in the San Francisco Bay Area with 5–6 years of experience spanning big tech (Google) and startups. Has owned large enterprise portfolios (80+ accounts) and delivered strong outcomes including 110% NRR, 98% retention, and a 60% reduction in onboarding time by building scalable playbooks. Also brings martech/SEO analytics experience and hands-on technical problem solving (including Python scripting to unblock third-party API integrations).”

“Analytics professional focused on procurement, supplier, and contract spend analytics, with hands-on experience using Snowflake SQL, Python, and Power BI to turn messy financial and vendor data into decision-ready reporting. They appear strongest in building reusable data workflows, defining business KPIs with finance/procurement partners, and validating results through reconciliation and stakeholder review.”

“ML/AI engineer with hands-on experience building healthcare and fraud-detection systems from experimentation through deployment, monitoring, and retraining. Stands out for combining real-time IoT pipelines, cloud-native MLOps, and GenAI/RAG in regulated healthcare settings, with reported impact including reduced emergency response times and a 25% reduction in manual diagnosis time.”