Iβm a data driven product leader with three successful startup exits across multiple industries. I have deep experience in healthcare spanning payer, provider, patient, and pharma. I turn complex clinical and operational problems into elegant, scalable solutions.
Jess Poeske
Product Management
π Pittsburgh, PA
Breadth of Experience
From early-stage startups to scaled enterprise platforms, each experience sharpened how I approach ambiguity, complexity, and user-centered decision making.
How I Work
I start with data to uncover real problems, move quickly through validation and delivery, and continuously loop learnings back into the system.
Click any step to explore.
Prioritization
There are LOTS of great frameworks β but there isn't a one-size-fits-all framework. The right choice depends on product maturity, scale, business type, and the specific context you're operating in. And no framework is a silver bullet that will solve every problem!
PRICE: An adapted framework PRICE
The PRICE framework is my adaptation of Intercom's RICE framework, modified to better fit enterprise and B2B products. This is how I adapt frameworks to the business context rather than applying them blindly.
PRICE Formula
(P Γ R Γ I Γ C) Γ· E
Potential β How potentially repeatable is this feature/use case for other customers?
Massive = 3 Β· High = 2 Β· Medium = 1 Β· Low = 0.5 Β· Minimal = 0.25
Revenue β How large of an annual revenue/value generator is this?
Massive = 9β10 Β· High = 7β8 Β· Medium = 5β6 Β· Low = 3β4 Β· Minimal = 1β2
Impact β How much will this impact each person?
Massive = 3 Β· High = 2 Β· Medium = 1 Β· Low = 0.5 Β· Minimal = 0.25
Confidence β How confident are you in your estimates?
High = 100% Β· Medium = 80% Β· Low = 50%
Effort β How many person-months will this take?
Use whole numbers; minimum 0.5 months
Sample PRICE Scoring
| FeatureFeat. | P | R | I | C | E | ScoreS |
|---|---|---|---|---|---|---|
| Centralized HIPAA LoggingHIPAA Logging | 3 | 3 | 3 | 90% | 1 | 24.3 |
| Governor 2.0Governor 2.0 | 2 | 6 | 2 | 90% | 1 | 21.6 |
| Data Quality EnforcementData Quality | 3 | 4 | 2 | 90% | 1 | 21.6 |
| Multi-layer PDF SupportPDF Support | 2 | 6 | 2 | 80% | 1 | 19.2 |
| Auto-detect Scanned ContentScanned Content | 2 | 6 | 2 | 80% | 1 | 19.2 |
| API Performance ImprovementsAPI Performance | 3 | 7 | 3 | 70% | 3 | 14.7 |
Roadmap
A real roadmap snapshot from Alexandria Charts, organized into thematic waves that balance customer value, security, and engineering health.
β± Stretch goal
Deep Dives
A selection of product work spanning 0β1 commercial launches, clinical AI strategy, and market strategy. These reflect the full breadth of my product leadership.
UPMC Enterprises Β· 0β1 Commercial Launch
Alexandria Charts is a foundational case study that demonstrates how I build products from 0β1. This project spans strategy, discovery, execution, and scale, reflecting the full breadth of product leadership.
View the Full Case Study βSince 2015, Health Fidelity used Alexandria Charts to build their Lumanent Retrospective Review tool for UPMC Health Plan's Medicare Advantage risk adjustment team. The company was acquired by Edifecs in December 2021.
M*Modal Β· Strategic Investment Recommendation
Nurses spend 2-4 hours per 12-hour shift entering 631-875 data points manually. 85% of nursing documentation is discrete data entry. I identified three AI product tiers to address this burden.
View the Full Case Study βThree investment paths with distinct return profiles:
Healthify Β· SDoH Platform
Healthify's referral network connected patients to community-based organizations for social needs β but the data sharing model created legal, ethical, and CBO recruitment challenges. This project revamped the permissions architecture to make data handling more transparent, compliant, and client-centered.
View the Full Case Study β
Maven Machines Β· Transportation Logistics
Maven Machines had a growing set of logistics products spanning two distinct markets. This project defined a cohesive portfolio strategy across LTL and Final Mile delivery, balancing competing resource demands and sequencing investments to seize market opportunity.
View the Full Case Study βTwo-market product portfolio:
Smith Micro Β· Subscription Growth
Facing sustained premium subscriber decline, I led a structured analysis of conversion funnel changes across product versions. The investigation surfaced a strong correlation between specific workflow changes and negative conversion trends β providing a clear, evidence-backed path to reversing the decline.
View the Full Case Study βAI Prototyping
I use generative AI tools to rapidly prototype product ideas, gather early user feedback, and iterate quickly without significant UX or engineering investment. Some projects even include full CI/CD pipelines. Below are a few examples built around problems from my own life.
UX + Design Work
In addition to rapid AI prototyping, I take a design first approach. These high level mockups, created in Figma, Balsamiq, and PowerPoint, helped explore product ideas and guide implementation. Clickable prototypes were often shared with stakeholders and beta customers to gather feedback before development.
The Human Behind the Product
Iβve spent my career building products in complex industries, helping early ideas grow into real companies. Iβm especially drawn to healthcare challenges where better systems can improve patientsβ lives while letting technology fade into the background.
Outside of product work, Iβm active in Pittsburghβs startup and arts communities and enjoy experimenting with new ideas and tools.
Customer and data first. Every decision anchored in user evidence and measurable outcomes, not opinions.
Frameworks are tools, not rules. The right framework depends on product maturity, business type, and context. No silver bullets.
Complexity is not the enemy. Some problems are hard. I lean into that complexity and build teams and systems that thrive in it.
Mission matters. I do my best work when the product I'm building has the potential to genuinely improve peoples' lives.
Open to product leadership roles in healthtech, AI-driven platforms, and mission-driven organizations.