Senior Product Manager, Custom Algorithms

We need to output HTML fragment with sections: About the role? Actually the posting includes sections: "Now, we’re growing! The Role" then "Location:", "What You’ll Do", "Who You Are", "Salary:", "What We Offer", "What You’ll Find at Cognitiv". Also "About the role" not explicit but we can treat "The Role" as heading? The instruction: use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to map content to those headings where appropriate. We should not repeat job title. We need to include sections only when posting has real specific content. We have: - About the role: maybe the introductory paragraph about Cognitiv and mission? Could be "About the role" but we have "Now, we’re growing! The Role". Could treat as About the role. - Responsibilities: "What You’ll Do" list. - Requirements/Qualifications/Skills: "Who You Are" includes many bullet-like paragraphs; we can treat as Requirements or Qualifications. Could split into Requirements and Skills? But we prefer few substantive sections. Could combine into "Requirements" with list. - Benefits: "What We Offer" includes benefits list. - Pay: Salary section. - Schedule: Location and hybrid schedule. We must not include filler like "commensurate with experience". Salary is specific: $175,000 - $210,000 Base Salary + Equity. Schedule: "Location: This position will be located in NYC, San Mateo, or Bellevue with a hybrid work schedule of 3 days in office (Mon/Tue/Wed) and 2 days remote optional (Thursday/Friday)." That's specific. We need to remove boilerplate: EEO, note on AI Use, etc. Also remove duplicated lines. We must preserve all substantive information. So we need to keep the details about role, responsibilities, who you are, salary, benefits, etc. We need to output only HTML fragment, no /, no markdown fences. We'll produce something like:

About the role

At Cognitiv, we are ... (the introductory paragraph up to "Now, we’re growing! The Role" maybe). Actually we need to include the description of Cognitiv and mission. Let's capture: "Are you ready to revolutionize the advertising industry? At Cognitiv, we are not just another AdTech company—we are industry trailblazers redefining media buying with our Deep Learning Advertising Platform. Since 2015, we have harnessed the power of cutting-edge deep learning technology and data science to transform how brands connect with their customers. Our mission? To bring intelligence to advertising and deliver unparalleled precision, relevance, and impact at scale. With our innovative platform, advertisers enjoy unprecedented flexibility—whether it is activating Dynamic Deals through their preferred DSP, leveraging our managed service DSP, or utilizing our industry-first ContextGPT product. As a part of Cognitiv, you will be at the forefront of AI-driven advertising solutions, driving change and achieving remarkable growth in a rapidly evolving industry." Then after that, "Now, we’re growing! The Role" maybe we can treat as part of About the role. Then responsibilities: list items from "What You’ll Do". We'll convert each bullet to

. Who You Are: list items. Benefits: list from "What We Offer". We'll need to capture each benefit item. Pay:

Pay

Salary: $175,000 - $210,000 Base Salary + Equity

Schedule:

Schedule

Location: This position will be located in NYC, San Mateo, or Bellevue with a hybrid work schedule of 3 days in office (Mon/Tue/Wed) and 2 days remote optional (Thursday/Friday).

We must not include sections like Requirements if we already have Who You Are as Requirements. Could use

Requirements

for Who You Are. We need to ensure we don't create empty sections. Let's extract responsibilities list: From "What You’ll Do": - End-to-End Strategy & Roadmap Ownership. Lead product strategy for Custom Algorithms from vision to execution. Prioritize high-impact features, evaluate incoming custom client requests strategically to determine if they are worth pursuing, and make the hard calls on what to ship, defer, or decline to keep the team focused. - Data Science & Engineering Partnership. Set the product goals models optimize toward, and agree on the quality bar a model must clear before launch with Data Science and Engineering. Build deep trust and credibility with the Data Science team while ensuring clear boundaries: Data Science owns the modeling approach, features, and technical execution; you own what good looks like and the product direction. - Performance Accountability. Monitor and analyze campaign performance to ensure algorithms perform at a high level. When campaigns underperform, size the commercial impact and drive prioritization with Science and Engineering through to resolution. - Adoption and Commercial Fit. Partner directly with Sales, Customer Success, and Product Marketing to drive uptake across the advertiser base. Support Sales on strategic client calls when deep product expertise is needed. Define which advertisers are a good fit, set clear performance expectations before a campaign launches, and know when to decline. - Scalable Delivery & Process. Drive down the manual effort and time required to launch each custom model, working with Data Science and Engineering to establish a repeatable, scalable process for running custom algorithms. - Market Analysis and Revenue Growth. Conduct market research to understand industry trends, evaluate how our product stacks up against competitors, and uncover new opportunities. Identify which types of customers we should be going after and how, determine which new KPI models to build, uncover new opportunities, and expand top-line growth. - Cross-Functional Leadership. Own the product point of view for Custom Algorithms across Data Science, Engineering, Sales, Customer Success, Product Marketing, and executive leadership. We'll make each as

. Who You Are list: - AI & ML Product Fluency. You've worked on products where Machine Learning and/or Deep Learning were the core of the value, so you know how they behave: data requirements, probabilistic output, performance that drifts. You keep current on what's becoming possible in AI and what it means for products like ours. You can judge whether a model is serving the product goal, push back when it isn't, and be taken seriously by the people who build it. - Commercial ML Track Record. You've owned ML products where the output was money, not a metric (e.g., driving measurable revenue growth). 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 tell 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 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 (or owned a significant, high-impact component of a complex technical product). Discovery through ship, with the tradeoff calls made on incomplete information. You write specs engineering can build from without follow-up clarification sessions. You're the accountable owner, not a coordinator. - Credible in the Room. You present with authority to advertisers and to executives, and you can hold a room when the news isn't good. - 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 and productized. - Familiarity with signal loss and privacy, including first-party data onboarding, clean rooms, and identity. - Enthusiasm for staying up to date with the latest AI technologies and trends and identifying ways to apply them to products. We'll make each as

under Requirements. Benefits list from "What We Offer": - Compensation is based on experience, skills, and other factors. Base salary is just one part of your total rewards at Cognitiv—you’ll also receive equity and a comprehensive benefits package. - Highlights Include 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! Also "What You’ll Find at Cognitiv" includes cultural aspects: Festiv, Responsiv, Inclusiv, Inventiv, Transformativ, Collaborativ. Those are also part of benefits/culture. Could include them under Benefits as well. We'll include them as list items. We need to avoid duplication: The "Compensation is based on experience..." is somewhat generic but still substantive. We'll keep. Now produce HTML. We'll start with

About the role

...intro...

Then

Responsibilities

...

Then

Requirements

...

Then

Benefits

...

Then

Pay

...

Then

Schedule

...

Make sure no extra whitespace? It's fine. Let's craft the intro paragraph: combine the first paragraphs up to "Now, we’re growing! The Role". Actually we can include that sentence as part of About the role. Intro: "Are you ready to revolutionize the advertising industry? At Cognitiv, we are not just another AdTech company—we are industry trailblazers redefining media buying with our Deep Learning Advertising Platform. Since 2015, we have harnessed the power of cutting-edge deep learning technology and data science to transform how brands connect with their customers. Our mission? To bring intelligence to advertising and deliver unparalleled precision, relevance, and impact at scale. With our innovative platform, advertisers enjoy unprecedented flexibility—whether it is activating Dynamic Deals through their preferred DSP, leveraging our managed service DSP, or utilizing our industry-first ContextGPT product. As a part of Cognitiv, you will be at the forefront of AI-driven advertising solutions, driving change and achieving remarkable growth in a rapidly evolving industry. Now, we’re growing! The Role" We'll put that in

. Now responsibilities list items as above. Now requirements list items as above. Now benefits list items: we need to capture each bullet. Let's list them: - Compensation is based on experience, skills, and other factors. Base salary is just one part of your total rewards at Cognitiv—you’ll also receive equity and a comprehensive benefits package. - Highlights Include 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