Senior Product Manager, Custom Algorithms
Summary
Owns Cognitiv's Custom Algorithms product end to end — roadmap, model quality, and the advertiser launch process — partnering with data science, engineering, and sales on a deep-learning advertising platform. Hybrid role (3 days in office) based in NYC, Bellevue, or San Mateo.
The Role
This role is accountable for the performance and scalability of Cognitiv's Custom Algorithms product by owning model quality, the advertiser launch process, and the roadmap end-to-end. You will work closely with data science, engineering, sales, and account management to deliver new products and features to drive revenue growth and customer retention.
Location: This position will be located in either NYC, Bellevue, or San Mateo with a hybrid work schedule of 3 days in office (Mon/Tue/Wed) and 2 days remote optional (Thursday/Friday).
What You’ll Do
- End-to-End Roadmap Ownership for Custom Algorithms. Lead product strategy, prioritize high-impact features, and make the hard calls on what to ship, defer, or decline.
- Data Science Alignment. Partner with Data Science on model quality, features, retraining cadences, evaluation metrics, and drift remediation.
- Root-Cause Diagnostics. Interrogate underperforming campaigns to isolate the core issue—data, model, or delivery—and execute the fix.
- Commercial Pre-Flighting. Set strict, clear performance expectations with Sales and CS before campaign launch to lock in client success.
- Pragmatic PRD Creation. Author crisp specifications that enable Data Science and Engineering to build, iterate, and ship high-value features fast.
- Scalable Delivery. Streamline the launch workflow to reduce manual touchpoints and accelerate time-to-market for custom models.
- Revenue Innovation. Uncover untapped market opportunities and build algorithmic products that directly expand top-line growth.
- Cross-Functional Leadership. Serve as the authoritative voice and champion for Custom Algorithms across internal teams and executive leadership.
Who you are:
- Deep ML & AI Literacy. You have real depth in machine learning. You reason fluently about training data, features, evaluation metrics, and retraining, enough to challenge a data scientist's assumptions and be taken seriously doing it. You don't need to build the models. You do need to understand why one is underperforming.
- Commercial ML Track Record. You've owned ML products where the output was money, not a metric. Recommendations, pricing, risk, fraud, search ranking, marketplace matching. High-volume inference, noisy feedback, and a real commercial consequence when the model is wrong.
- Technical Translator. You translate model behavior into commercial language. You can explain to an advertiser why their conversion volume isn't enough to train on, and to a sales lead what "good" looks like before the deal is signed. This is the highest-leverage skill in the role.
- Analytically Self-Sufficient. You're analytically self-sufficient. You pull and interrogate performance data yourself. Given an underperforming campaign, you arrive with a hypothesis, not a request for someone else to look into it.
- Accountable Product Owner. You've owned a technical product end to end. Discovery through ship, with the tradeoff calls made on incomplete information. You're the accountable owner, not a coordinator.
- Master Communicator. You synthesize complex algorithmic systems into compelling narratives that align internal executives and instil confidence in external clients.
- Proven Track Record. 5+ years in Product Management, or in data science / ML engineering with direct product ownership
Bonus Points If You Have:
- Programmatic advertising experience, including bidding and auction mechanics, campaign KPIs, and attribution
- Causal and experimental rigor. You can design a holdout, reason about selection effects, and tell whether a model is creating outcomes or just finding people who would have converted anyway
- A hands-on modeling background, or you still write SQL and Python
- Experience turning a bespoke, specialist-delivered offering into something repeatable
- Familiarity with signal loss and privacy, including first-party data onboarding, clean rooms, and identity
Salary:
$175,000 - $210,000 Base Salary + Equity
What We Offer
- Medical, Dental and Vision plan for US employees & Extended Health Benefits for Canadian employees
- 12 weeks paid parental leave + 4 weeks WFH
- Unlimited PTO + Work-From-Anywhere August
- Career development with clear advancement paths
- Equity for all employees
- Hybrid work model & daily team lunch
- Health & wellness stipend + cell phone reimbursement
- 401(k) & RRSP with employer match
- Parking (CA, WA, Vancouver offices) & pre-tax commuter benefits
- Employee Assistance Program
- Comprehensive onboarding (Cognitiv University)
- …and more!
What You’ll Find at Cognitiv
- Festiv – We make work fun with cross-team games, events, and creative team bonding.
- Responsiv – You’ll be close to clients and leadership, influencing real outcomes.
- Inclusiv – Diversity and individuality are celebrated across all levels.
- Inventiv – We reward curiosity and embrace bold ideas.
- Transformativ – We support your growth with training, mentorship, and flexibility.
- Collaborativ – We operate across coasts, connected by purpose and teamwork.
Skills
As published by greenhouse · 12 questions · 4 written answers
Basics
First Name, Last Name, Email, Phone, Resume/CV, Cover Letter, Location
Short answers (2)
- Preferred First Name optional
- LinkedIn Profile
Pick from a list (6)
- Do you have 5+ years of experience as a Product Manager?
- Which best describes how you use AI in your work today?
- We have a hybrid culture. Are you able to work out of our office Monday, Tuesday and Wednesday?
- Are you legally eligible to work in the United States today and in the future?
- Do you require sponsorship to work in the United States?
- The base salary for this role is $175,000 - $210,000 USD + Equity. Does this align with your compensation expectations?
Written answers (4)
- Why Cognitiv? Why are you interested in this role with us?
- This role requires a deep machine learning or deep learning product background. Please briefly describe your experience owning ML/DL products.
- Have you directly owned an ML/AI-powered product or feature where model performance had a measurable commercial impact (e.g., revenue, conversion, pricing, fraud loss, retention, etc.)? If yes, briefly describe the product, your role, and the commercial outcome.
- Do you have experience working in the AdTech industry? If yes, please share the AdTech companies you have worked for and briefly describe your experience.
