Optimizely
Manager, Product Management

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We're not here to add to the noise. We're here to cut through it - with AI that actually works for marketers.
From AI-powered content creation to world-class CMS and the industry's most trusted experimentation platform, Optimizely is the tool modern marketers actually want to use. AI-Ready. Set. Go.
10,000+ brands including H&M, PayPal, and Zoom already get it. So do Gartner, Forrester, and IDC, who consistently recognize us as leaders in MarTech.
But here's the thing about building great products: it takes great people. Our 1,600+ Optimizers across 12 global offices are curious, collaborative, and refreshingly human. We don't do corporate speak. We do real conversations, big ideas, and genuinely care for the work we make together.
If you want to be part of a team that's shaping the future of marketing technology — and actually enjoys doing it — you're in the right place.
Find us on Instagram: @optimizely
Introduction
We're looking for a Manager, Product Management for Optimization Analytics - the metrics, statistics, events, and reporting that tell our customers whether what they shipped across experimentation, personalization and feature management worked.
You'll own product strategy and execution for Optimization Analytics: the measurement and reporting layer underneath every experiment, feature rollout, and personalization campaign we run. You'll also build and lead a team of three - two statisticians and a product manager to begin with. This is a player coach role where you would be responsible for guiding the direction of our statistics and program ROI product developments while leading efforts around metrics, results, and new AI agent development.
You'll help define what this function looks like in the age of AI. As a company, we have heavily invested in agentic workflows across our products, and this role would own agentic optimization analytics to identify interesting segments, detect anomalies, build readout reports, and more.
Job Responsibilities
People Leadership & Team Development
- Lead a team of two statisticians and a product manager, building career paths for a technical, customer-facing function that blends deep statistical rigor with product ownership.
- Set clear goals and quality standards for both product and technical work, including work you don't personally produce.
- Build a team culture where statisticians and PMs collaborate effectively together to build better product.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Product Strategy & Roadmap
- Own the roadmap for Optimizely's measurement and reporting capabilities: the metrics catalog, statistical engine, events pipeline, and program ROI reporting that customers and internal teams depend on.
- Partner with Product leadership to connect this roadmap to the broader experimentation and personalization portfolio, so every product tells a consistent, defensible story about impact.
- Use customer and market signals to prioritize investment across statistical rigor, self-serve reporting, and program-level ROI storytelling.
Statistical Rigor & Methodology Oversight
- Act as a credible thought partner to your statisticians: understand the tradeoffs across classical, Bayesian, and causal-inference approaches well enough to review their work, defend it to customers, and know when to push back.
- Set and enforce standards for statistical validity across the platform, protecting the credibility of every result Optimizely surfaces.
- Recognize when a statistical question needs deeper expertise than you can personally provide, and route it to the right person without slowing the team down.
Customer & Cross-Functional Engagement
- Get in front of customers to explain how we protect statistical accuracy, and to hear directly what's blocking their confidence in the numbers.
- Partner with Engineering, Design, Product Marketing, and Customer Success to ship reporting and measurement capabilities customers actually use.
- Represent your team's work to Product leadership, translating statistical nuance into a story executives and customers can act on.
AI & Agent-Driven Innovation
- Build and ship agents that do real statistical and analytical work — catching sample ratio mismatches, estimating power, recommending metrics, or surfacing root causes — not just summarizing dashboards.
- Set the bar for how your team uses AI day to day, so agents become part of how the work gets done, not a side project layered on top of it.
- Partner with our AI product and engineering teams to make sure analytics and statistics are full citizens of Optimizely's broader AI strategy.


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Knowledge and Experience
- 5+ years of Product Management experience, including 2+ years directly managing product managers, statisticians, data scientists, or other technical individual contributors.
- Comfortable partnering with a statistics team - you don't need to derive the models yourself, but you understand classical inference, Bayesian methods, or causal inference well enough to be a credible reviewer and thought partner.
- Hands-on experience building AI agents or agentic workflows, not just directing others to use AI tools; you can speak to specific agents you've built, the tradeoffs you made, and what you'd do differently.
- A track record of owning a product area end to end: setting strategy, shipping, and proving impact with data.
- Strong technical acumen with data infrastructure, metrics systems, or reporting platforms; comfortable in ambiguity where "the right answer" is a judgment call, not a formula.
- An excellent communicator who can translate statistical nuance for engineers and executives alike, and who builds trust quickly with a team whose expertise differs from their own.
- Highly collaborative and self-motivated, with experience managing a small, technically deep team across time zones.
Why Join Us
- Lead the team responsible for the numbers behind every Optimizely experiment, feature rollout, and personalization campaign — the function that decides what "it worked" really means.
- Help define what an AI-native analytics and statistics practice looks like, with real agents doing real work.
- Build and grow a team from the ground up, shaping both its people and its product.
- Work alongside statisticians, engineers, and product leaders who care deeply about getting the numbers right.
- Join a company recognized by Gartner, Forrester, and IDC as a leader in MarTech, at a moment when analytics is one of our biggest growth bets.
Education
- Bachelor's degree or equivalent working experience.
Optimizely is committed to a diverse and inclusive workplace. Optimizely is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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