Senior Product Manager · New York, NY

Maria
Fernanda
Flores

I build products at the intersection of operations, data, and growth. I never stop asking why.

5+
Years
PM, Ops & Strategy across tech, logistics & consulting
4
Global Markets
U.S., Mexico, Canada, Brazil
30%
Inquiry Reduction
LLM system replacing PM interrupt work
$70K
Annual Savings
Through onboarding pre-qualification design

Built to ask why.

I'm a Senior PM with a background that spans product, operations, and strategy. I've spent the last five years building and scaling platforms at Draiver — starting by standing up a 30-person Customer Operations function from scratch, and transitioning into owning a portfolio of five B2B and B2C products across four international markets.

What drives me isn't the output. It's the mechanism behind it. I'm the person who can't walk past a problem without wanting to understand its structure. Not to be difficult, but because the why usually contains the entire solution.

How I actually think

A few years ago, waiting at a pizza place with a friend, we started wondering how many pizzas they sell in a day. By the time we reached the cashier, we'd worked through the line length, average wait time, peak lunch and dinner windows, the ratio of whole pies to slices, and a per-day-of-week adjustment. We asked the person at the register for the actual number before placing our order. That's not a professional exercise. That's just how my brain works. The analytical instinct doesn't turn off. I'm always looking at what drives a business, what made someone build it, and what the ceiling on its growth actually is.

Before Draiver, I was a strategy consultant at Nepanoa in Guadalajara. One of my clients was Draiver. They needed someone to go boots-on-the-ground and lead their Mexico market pilot, a high-visibility engagement tied directly to an acquisition they were pursuing. I led it. The pilot worked. When the acquisition closed, they asked me to stay and build the Customer Operations function from scratch. I was the consultant they trusted enough to hire. That consulting chapter, learning to move fast in ambiguous environments, communicate to executives, and turn operational chaos into structured plans, is the foundation everything else is built on.

Currently
Senior Product Manager at Draiver · New York, NY
Targeting PM, Product Ops, and Strategy roles in NYC
Background
BS Industrial & Systems Engineering, Tecnológico de Monterrey (one of Latin America's top-ranked engineering programs) · Exchange semester, Boston University
Languages
Bilingual English / Spanish · Conversational German (Goethe B1)
Expertise
0→1 Product AI / LLM Integration Logistics & Marketplace Global Expansion Product-Led Growth Ops → Product B2B & B2C Agile / Scrum

What I bring to the table.

Product
End-to-end lifecycle (0→1)
Product strategy & OKRs
Roadmapping & prioritization
Product-led growth
AI / LLM integration
Discovery & user research
Cross-functional delivery
Technical
SQL
REST APIs
Amazon SQS
AWS microservices
Jira & Confluence
Salesforce (admin)
NetSuite integration
Operations
CRM administration
SOP design & documentation
Process optimization
KPI tracking & reporting
Agile / Scrum
Support ops & CSAT
Team building (0→30)
Strategy
TAM sizing & market entry
Competitive benchmarking
Stakeholder communication
Executive reporting
Risk assessment
International expansion
M&A project support

Selected work.

Each project is documented with the problem, my specific role, how it worked, and what I learned. Click any card to expand.

The Problem

Four PMs were collectively fielding ~40 inbound status questions per week from Sales, Ops, CS, and the C-suite, with no formal intake process. Each response required manually pulling Jira, cross-referencing the roadmap, calculating queue position using point/effort equivalencies, and writing a personalized reply. That was 5–8 hours of unplanned interrupt time weekly.

My Role
  • Problem diagnosis: audited 6 weeks of inbound Slack and email threads to categorize question types
  • Data architecture: mapped the three source-of-truth systems the LLM needed to query (Jira, roadmap doc, sprint calendar)
  • API integration & prompt design: worked alongside engineering on Jira API integration and LLM prompt templates
  • Output design: defined the structured Slack/email response format including sprint dates, effort estimates, and reprioritization context
  • Rollout: ran a two-week pilot with CS and Ops teams; added confidence threshold routing before company-wide launch
What I Learned
The bottleneck was translation, not access

The data existed in three places. The problem was that converting it into a useful answer required PM context stakeholders didn't have. That's exactly what an LLM handles well.

Confidence thresholds matter more than accuracy averages

Early versions had a higher auto-response rate. A few wrong answers caused more trust damage than the time savings justified. Adding a routing threshold for low-confidence cases was the most important quality decision.

Documentation quality becomes a product dependency

The system was only as good as the ticket comments it indexed. This created an unexpected forcing function: PMs became more disciplined about logging reprioritization rationale because they knew it would surface directly to stakeholders.

Revenue · Growth

Self-Serve Move Pricing Tool

Replaced manual Excel quotes with a public-facing estimator covering 4 countries, 3 move types, distance calculation, and vehicle compliance rules. Lead capture and demand signal tracking built in from day one.

Days→Min
Quote turnaround (projected)
4
Markets supported
Expand case study →
Operations · 0→1

Customer Operations: 0 to 30-Person Team

Built the entire Customer Operations function at Draiver from scratch: team, CRM, dashboards, knowledge base, SOPs, and a data bridge to product that turned support tickets into a product feedback loop.

70%
Support volume reduction
50%
FCR improvement
Expand case study →
The Problem

Prospective clients had no way to understand Draiver's pricing without scheduling a sales call. Every quote was built manually in Excel: pulling rate cards, calculating distances, applying the right country/move-type price list. There was no self-serve option, no structured lead capture, and no data on what the market was actually asking for.

How It Worked
  • User inputs Point A and Point B → distance calculated automatically
  • Selects move type (Fleet, Consumer, Automatic Retail) and country
  • Flags vehicle compliance requirements (CDL / DOT medical card)
  • The system queries the back-end price list for the selected move type, country, and compliance flags and returns a single calculated estimate
  • Price lists are managed directly by the sales team via a back-end interface, so adjustments can be made immediately without a dev release
  • User enters name and email → quote stored and tied to their lead record
  • CTA to book a sales call or submit a move request directly
Projected Value
Quote turnaround: days → under 2 minutes

Eliminates the Excel quoting step for initial estimates. Projected ~20–30 min saved per qualified lead for the sales team.

Demand signal for pricing review

First-ever structured view of which routes, move types, and markets generate the most exploration vs. conversion. A direct input for Sales and Finance pricing reviews.

Every lead arrives with a stored quote

Salespeople enter conversations knowing what the client priced, what estimate they saw, and what compliance flags they selected. No cold starts.

Note: tool launched in testing phase. Figures are projected; actuals to be updated as data accumulates.

The Problem

Draiver was scaling rapidly with no formal Customer Operations structure. There was no CRM, no knowledge base, no SOPs, and no consistent way to handle support tickets. The product and ops teams had no visibility into what users were struggling with, and there was no mechanism to turn that signal into product improvements.

What I Built
  • Hired and onboarded a 30+ person support team in a high-growth startup environment
  • Designed and deployed the CRM from scratch: custom dashboards, automated reporting, ticket volume and resolution tracking
  • Built the company's first internal and user-facing knowledge base from cross-functional user interviews and standardized SOPs
  • Created a data bridge between CRM and Product that surfaced UX friction points as product requirements, reducing registration support volume by 70%
  • Synthesized weekly QA intelligence for C-suite, improving procedural accuracy by 16%
Why It Mattered
Ops as the earliest product signal

A 70% drop in registration support volume didn't come from better scripts. It came from identifying root-cause UX friction points and turning them into product fixes. The ops function was the most direct feedback loop into the product roadmap at that stage.

The CRM is a product too

Designing the CRM and dashboard infrastructure around the GTM team's actual decision-making needs, not just ticket volume, is what made it stick. It's still the system the team runs on today.

From ops to product: the through-line

This role taught me that the transition from ops management to product management isn't a pivot. It's an evolution. The same instinct that builds a good SOP builds a good product spec.

The Situation

Draiver was pursuing an acquisition and needed to validate their model in a new international market before the deal closed. I was a strategy consultant at Nepanoa at the time, and Draiver was one of our clients. They needed someone who could go on the ground in Mexico, embed with the client's operation, and make the pilot work. I was the person they put on the ground.

What I Did
  • Embedded directly with the client's dispatchers and drivers, operating as the bridge between Draiver's product and the on-the-ground operation
  • Built a complete, improved training program in English from scratch, then translated it fully into Spanish. This was Draiver's first Spanish-speaking client, and the materials went on to train employees across future pilots and rollouts, as well as the customer support team
  • Ran the full pilot training cycle and proactively identified operational gaps on both the Draiver side and the client side, surfacing what needed to change internally and externally to hit the productivity targets
  • Increased throughput from 1.2 to 4 units/day, a 230% improvement over the course of the engagement
  • Project-managed the full expansion across all workstreams: reviewing documents and deliverables, tracking bugs, coordinating tech access, aligning stakeholders from multiple teams, delivering weekly status reports, and calling out blockers and delays before they became problems
  • Built the operational documentation and playbook that became the template for subsequent market expansions
  • Presented pilot results to C-suite leadership at both Draiver and the client, under acquisition scrutiny from multiple stakeholders
What Happened Next
The pilot contributed to the acquisition closing

The Mexico engagement was one of the proof points the deal depended on. Demonstrating that the model could work in a new market, with a new language and client, mattered to the outcome.

Draiver's CEO hired me out of consulting

After the acquisition closed, Draiver's CEO asked me to join full-time and build the Customer Operations function from scratch. By that point I had earned the confidence of the entire C-suite. They had all been part of the pilot's progress reports and had seen firsthand how it was handled. I transitioned from external consultant to founding operator. The 0 to 30-person ops team, the CRM, the SOPs, all of that came next.

What this engagement taught me about operating under pressure

I was evaluated under real acquisition stakes, by real decision-makers, before they committed to me full-time. Being trusted enough to be hired away from the consulting firm is the signal I'm most proud of. The work spoke clearly enough that they didn't want to stop working with me.

What I build when I'm curious.

These are tools I built for myself to solve real problems in my own job search and interview prep. Each one is a working application built entirely with AI as a development collaborator.

⚙️
Job Hunter OS: AI Resume & Application Tracker

A single-file, locally-hosted web app that turns a job search into a structured, AI-assisted workflow. Includes a Role Analyzer (ATS score, H1B signal, salary intel), Resume Tailor, ATS Re-Scorer, Cover Letter generator with version history, Cold Outreach module, and a full Application Tracker. Every step carries data forward so nothing needs to be re-entered. Built specifically for a Senior Manager / Director-level PM search in NYC.

Vanilla JSClaude APIStreaminglocalStorageSingle-file
Read the case study ↗
GitHub ↗ Live Demo
🎯
Interview Case Coach: Business Operations & Strategy Prep System

A suite of three tools for decomposition-style case interview prep, built specifically for consulting and business operations roles. The Decomposition Interview Guide covers 12 case scenarios with the full logic flow an interviewer expects, the clarifying questions a strong candidate should ask, and a side-by-side red flags vs. strong signals grid for each case. The Candidate Model Answers document works through all 12 cases as live candidate-to-interviewer dialogue, with alternative approaches rated weak, acceptable, or strong so you understand not just the ideal path but why weaker paths fail. The Case Coach is the active practice tool: paste any case prompt, work through all 7 framework phases, and get specific AI feedback at each step plus a 35-point readiness score at the end.

Claude APIDecomposition frameworkBizOps & StrategyAI feedback
Read the case study ↗
GitHub ↗ Live Demo
📰
Personal Daily Digest

A custom daily briefing tool that aggregates news and content across only the topics I care about: business, product, tech, and market trends. I stay educated without spending time switching between tabs or scrolling through noise. Built as a personal AI workflow to reclaim the time I was previously losing to unfocused reading.

Claude APIContent curationPersonal workflow
📚
AI Certifications & Coursework

Actively building technical depth in AI — completing Anthropic's prompt engineering and LLM integration curriculum, and recently earned the Databricks Academy certification in AI Agent Fundamentals (score 80%+), covering agentic workflows, multi-agent systems, and enterprise AI on the Mosaic AI platform. Relevant to how I think about AI product implementation, not just theory.

Prompt engineeringLLM patternsAI AgentsDatabricks certified
View certificate ↗
📐
Market Sizing for Fun

Not a formal project, but worth noting. I regularly use estimation and market sizing as a game. Pizza places, coffee shops, subway foot traffic, retail conversion rates. The analytical instinct runs constantly. It's the same muscle that makes me useful in a product discovery session or a strategy meeting, and it genuinely doesn't turn off.

Fermi estimationMental modelsAlways on
🌎
Bilingual Professional

Fluent in English and Spanish, with conversational German (Goethe B1). Having built and scaled products across the U.S., Mexico, Canada, and Brazil, working across languages and cultures isn't a line on a resume. It's how the actual work got done. International product expansion is something I understand from direct experience, not theory.

EnglishSpanishGerman (B1)4 markets

What colleagues say.

From people who worked with me directly — managers, peers, and cross-functional leaders — across operations and product.

"
What sets Fernanda apart is her remarkable role flexibility. She has seamlessly navigated multiple business units — stepping in as an individual contributor when the work demands deep, hands-on focus, and shifting into a leadership role when teams need direction and alignment.

She also has a genuine desire to understand not just the problem she's solving, but the product itself. She digs in, asks the right questions, and builds a thorough understanding of the business and the people involved — making her an invaluable partner to every cross-functional team she works with.
Kevin Burke
Chief Technology Officer, DRAIVER · Cross-functional Peer
Verify on LinkedIn ↗
"
Fernanda brings strong product thinking, clear strategy, and a deep focus on user needs, consistently driving better outcomes and adoption.

She navigates complex priorities well, balancing new features with system stability, and is excellent at spotting process improvements that boost team efficiency and delivery. Fernanda actively looks for opportunities to add value, even in unfamiliar spaces, and steps up to make an impact.
Ryan Auf Der Heide
Chief Product Officer, The Good Game · Former Direct Manager
Verify on LinkedIn ↗

Let's talk.

I'm actively exploring Senior PM, Product Operations, and Strategy roles in NYC. If you're working on something interesting, or if you're a recruiter with a role that's a real match, I'd like to hear from you.

Available for new roles

Senior PM, Product Ops & Strategy roles in NYC

5+ years across logistics, marketplace, and consulting. Bilingual. Built products from 0 to 1 and scaled them across four international markets. Comfortable with technical depth and executive communication.

Send me an email →