Senior Product Manager, Custom Algorithms
About this role
Professionals who thrive in analytical, cross-functional environments where machine learning drives direct commercial outcomes will find a strong fit leading the Custom Algorithms product at Cognitiv. The team operates at the intersection of deep learning and programmatic advertising, building systems that optimize complex media buying decisions. In this capacity, you will own the entire lifecycle of the Custom Algorithms product, setting strategic roadmaps, defining optimization goals, and scaling processes alongside data science and engineering teams.
Driving adoption and revenue growth requires translating intricate model behavior into clear commercial concepts for sales teams and advertisers. The position exists to scale bespoke product offerings while maintaining strict performance standards and expanding top-line revenue. Successful candidates bring a rigorous technical background in machine learning products, combined with the commercial clarity needed to guide strategy and build trust across engineering, sales, and executive leadership.
What you will do
- Lead product strategy and execution for the Custom Algorithms portfolio from initial vision to final delivery.
- Partner with data science and engineering to establish model optimization goals and define launch quality bars.
- Monitor campaign performance to analyze algorithm effectiveness and drive prioritization for underperforming initiatives.
- Collaborate with sales, customer success, and product marketing to secure market adoption and drive revenue growth.
- Streamline the model launch process with engineering teams to reduce manual effort and achieve scalable delivery.
- Conduct market analysis to evaluate competitive positioning, industry trends, and new revenue opportunities.
What you need
- Bring five or more years of experience in product management or in data science and machine learning engineering with direct product ownership.
- Demonstrate fluency in artificial intelligence and machine learning products, including data requirements and probabilistic model behaviors.
- Possess a commercial track record of managing machine learning products where outputs drive measurable financial growth.
- Act as a technical translator who clearly communicates model capabilities and limitations to both technical teams and advertisers.
- Remain analytically self-sufficient by independently pulling and interrogating performance data to form hypotheses.
- Operate as an accountable product owner who writes precise specifications and manages end-to-end product delivery.
Nice to have
- Programmatic advertising experience, including bidding and auction mechanics, campaign KPIs, and attribution.
- Causal and experimental rigor, such as designing holdouts and reasoning about selection effects.
- Hands-on modeling background or the ability to write SQL and Python.
- Experience turning bespoke, specialist-delivered offerings into repeatable and productized solutions.
- Familiarity with signal loss and privacy, including first-party data onboarding, clean rooms, and identity.
Benefits
- Medical, Dental and Vision plan for US employees
- 12 weeks paid parental leave + 4 weeks WFH
- Unlimited PTO + Work-From-Anywhere August
- Equity for all employees
- 401(k) with employer match
- Health & wellness stipend + cell phone reimbursement
Skills and tech stack
Questions candidates ask
What is the remote work and office policy for this role?
This position is located in NYC, San Mateo, or Bellevue with a hybrid work schedule of 3 days in office on Monday, Tuesday, and Wednesday, alongside 2 days of optional remote work on Thursday and Friday.
What is the salary range and total compensation structure?
The base salary ranges from $175,000 to $210,000. In addition to base pay determined by experience and skills, total rewards include equity and a comprehensive benefits package.
How does the product team collaborate with data science and engineering?
You will set the product goals models optimize toward and agree on the quality bar a model must clear before launch with Data Science and Engineering. Data science owns the modeling approach, features, and technical execution, while product management owns what good looks like and the overall product direction.
What kind of hiring and AI review processes does the company use?
Cognitiv may use AI technology to assist with administrative aspects of the hiring process such as note-taking, interview documentation, and reporting. However, every resume and application is reviewed directly by the recruiting team without AI influencing candidate evaluation.