Senior Product Manager, Custom Algorithms

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. Must not repeat job title. Must not include Job ID etc. Must remove boilerplate, EEO, etc. Must preserve all substantive info. We need to parse the posting. Key sections: - About the role: The first paragraph after "Now, we’re growing! The Role" maybe. Actually the posting includes: "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." That's about the company and role overview. Could be "About the role". We'll put that as

About the role

with

containing that paragraph. - Location and 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)." This gives location and schedule. Schedule section: we can include schedule details. Pay section: Salary: $175,000 - $210,000 Base Salary + Equity. Also mention compensation based on experience etc. We'll include Pay section with that salary range and note equity. - Responsibilities: The "What You’ll Do" bullet list (actually paragraphs). We'll extract each bullet as

. The content includes multiple paragraphs each starting with bold headings. We'll treat each as a list item. - Requirements/Qualifications/Skills: The "Who You Are" section lists many bullet-like items. Could be split into Requirements, Qualifications, Skills. But we need to decide. The instruction: prefer a few substantive sections over many thin ones. Could combine into one "Requirements" section with list. Or separate into Qualifications and Skills if distinct. The "Who You Are" includes AI & ML Product Fluency, Commercial ML Track Record, Technical Translator, Analytically Self-Sufficient, Accountable Product Owner, Credible in the Room, Proven Track Record, Bonus Points If You Have..., etc. These are qualifications/skills. We could make a single "Requirements" section with list. - Benefits: The "What We Offer" section lists many benefits. We'll make Benefits section with list. - Also there is "What You’ll Find at Cognitiv" with values like Festiv, Responsiv, etc. That's more culture; could be part of Benefits or maybe separate but not required. Could include as part of Benefits or maybe as a separate section "Culture". But we only have allowed headings list; we could put under Benefits or maybe as a separate "Benefits" includes those. However those are not benefits per se but cultural aspects. Could still be included in Benefits as list items. We must not include boilerplate like EEO, note on AI use, etc. We must not repeat job title. We must not include duplicated lines. We must preserve all substantive information. Let's extract content. About the role paragraph: The first big paragraph up to "Now, we’re growing! The Role". Actually the "Now, we’re growing! The Role" is a heading but we should not repeat job title. The "About the role" could be the paragraph before "Now, we’re growing! The Role". 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." That's good. Now "What You’ll Do" section: list items: - 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. Now "Who You Are" section: list items: - 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. Now "Salary: $175,000 - $210,000 Base Salary + Equity". Also "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." Now Benefits: "What We Offer" list: - 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" list: - 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. These could be part of Benefits or maybe a separate "Culture" but not in allowed headings. Could include under Benefits as additional items. We must not include boilerplate like EEO, note on AI use. Now 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)." So we can have Schedule section with that sentence. Pay section: Salary range and note equity. Now we need to decide which sections to include: About the role, Responsibilities, Requirements (or Qualifications/Skills), Benefits, Pay, Schedule. We could combine Requirements and Skills into one "Requirements" section list. We must not create empty sections. Now produce HTML fragment: use

for each section heading, then

for prose,

• for lists. We need to ensure we don't include any markdown fences. Let's craft. First, About the role:

  About the role

  ...

  Second, Responsibilities:

  Responsibilities

  • ...
  ...
  Third, Requirements:

  Requirements

  • ...
  ...
  (include all Who You Are items). Fourth, Benefits: <