#job-search

I've been knee‑deep in building a PLG‑centric B2B SaaS stack for the past 18 months – think custom OKR tracking, automated CAC/LTV dashboards, and a 3‑month churn‑reduction sprint that lifted ARR by ~22% for a $12M seed‑stage company. The playbook is solid: segmented TAM analysis, buyer‑persona sequencing, and a beta‑to‑paid conversion funnel built on HubSpot + Mixpanel.

Now I'm looking to step up into a senior product lead role where I can own the full P&L and steer a new vertical launch. My résumé reads like a checklist of growth‑hacking metrics, but I haven't cracked the networking side yet. Any tips on:

• Pitching a playbook to VPs of Product without sounding like a sales script?
• Highlighting quantitative wins (e.g., 3‑point uplift in NRR, 1.8× CAC payback) in a way that catches a hiring manager's eye?
• Getting warm introductions to seed/Series A founders who need a product strategist now.

If anyone's willing to make a quick intro or share a template that worked for them, I'd owe you a coffee (virtual or real) and will gladly give back with a deep dive into my analytics framework. Thanks for any leads or advice – I'm keeping the hustle low‑key but the ambition high.

When the Fed ramps up QE and the VIX spikes, the traditional CAPM framework can mislead. Here’s a quick refresher on tightening it:

1. Update the market beta – use the 3‑month T‑Bill as risk‑free and the S&P 500’s 3‑year rolling return to adjust for a slower recovery.
2. Add a liquidity premium – during a downturn, institutional money prefers liquid assets. Apply a 2‑percentage‑point shift to the market premium.
3. Incorporate the TIPS spread – inflation expectations affect fixed income bets. The spread between 10‑yr TIPS and 10‑yr nominal rates usually correlates with equity volatility.
4. Use the Bloomberg Market Explorer (BME) v2.3 – its real‑time scenario engine helps simulate different QE phases and see how beta evolves.

Example: I ran a back‑test on a portfolio of 25 private‑equity funds during the 2021‑2022 downturn.

• Base beta: 1.45
• Liquidity adjustment: +0.20
• TIPS premium: +0.05
• Final adjusted beta: 1.70

That gave an expected alpha of 3.2 % above the benchmark after the first 12 months, which aligns with industry reports on PE post‑recession performance.

Now, on a slightly more personal note – I’ve spent the last eight years modeling these scenarios for institutional clients, and the next step for me would be a senior analyst position in a firm that values data‑driven private equity strategies. If anyone’s hiring or can point me to an opportunity where this skill set is prized, let’s connect. I’m open to full‑time and contract roles, and I can jump straight into a portfolio review within 30 days.

Questions are welcome – or feel free to message me privately if you think my background matches your needs.