Director, Data Product and Growth Strategy

We need to output HTML fragment with sections for headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections where there is real specific content. Must not repeat job title. Must not include Job ID etc. Must remove boilerplate, navigation, legal, EEO, etc. Must preserve all substantive info. Must not invent or summarize away detail. Must not include placeholder text like "commensurate with experience". Must not create Pay/Schedule/Benefits unless posting actually states them. Let's parse the posting. First paragraph: "At LegitScript, we are passionate about making the internet and payment ecosystems safer and more transparent. We help companies of all sizes keep their services legal and safe for consumers. To do this, LegitScript combines big data with the world’s leading team of experts skilled in highly regulated and complex sectors, including transaction laundering detection, pharmaceuticals, online gambling, and more. The result? Unmatched accuracy and deep risk analysis that identifies which commercial entities play by the rules, and which do not. Our diverse industry partnerships provide unique insights that keep businesses and governments at the forefront of emerging trends. That’s why LegitScript is trusted by the world's largest search engines, internet platforms, payment companies, and regulatory agencies." That's about the company, could be "About the role"? Actually "Overview" heading appears later: "Overview LegitScript's next stage of growth starts with finding it. The Director, Data Product and Growth Strategy owns that search: the next vertical, the size of the opportunity, the shape of the competitive field, and the business case that turns a market signal into a funded product. This is a strategy role with commercial accountability, not a research role. Success is measured in revenue paths opened, not documents produced. You will own the front half of the product lifecycle — market problems, segmentation, positioning, pricing, and portfolio direction — and hand validated, quantified opportunities to product management and engineering for execution. You will also build the mechanism that moves market intelligence through LegitScript: collecting customer, competitive, and partner signals on a regular cadence, turning them into a point of view, and pushing that point of view up to the executive team and down into roadmaps." That's description of role. Could be "About the role" or "Overview". The instruction says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we need to map content to these headings. Likely "About the role" for overview. Then "Responsibilities" for "What You'll Do". Then "Requirements" and "Qualifications" maybe combined? The posting has "What You'll Bring" which includes required experience and skills. Could split into Requirements (must-have) and Qualifications (preferred) or Skills. But we need to follow instruction: Use headings only when posting has real specific content. We can decide to have sections: About the role, Responsibilities, Requirements, Skills, Benefits (if any), Pay (if any), Schedule (if any). The posting mentions "LegitScript offers competitive compensation, flexible work options, and a team that's genuinely invested in your success." That's benefits and compensation. It mentions "competitive compensation" but not specific numbers. That's vague; we should not create Pay section unless posting actually states them. It says "competitive compensation" which is generic; maybe we should not create Pay section because it's not specific. Benefits: "flexible work options" and "team that's genuinely invested in your success" maybe considered benefits. Could include Benefits section with those. However "flexible work options" is a benefit. Also "competitive compensation" is vague; we should not create Pay section. Schedule: not mentioned. So we may omit Pay and Schedule. Now we need to extract substantive info for each section. About the role: Should include overview paragraph(s) describing role purpose, mission, etc. Could combine the first paragraph about company and the overview paragraph. But we should not repeat job title. We'll include description of role and company context. Responsibilities: The "What You'll Do" bullet list (actually sentences). We need to convert each duty into

. Must preserve all substantive info; do not summarize away detail. So we need to list each responsibility as separate

. The text includes many responsibilities separated by periods. We need to split them into list items. Let's extract: - Identify and validate new verticals, categories, and product offerings that expand LegitScript's addressable market beyond current lines of business. - Discover and validate market problems through structured interviews with customers, recent evaluators, and untapped prospects, backed by evidence rather than anecdote. - Map the competitive and alternative-solution landscape, including emerging entrants and adjacent-category threats, and develop a strategy for winning against each. - Build a repeatable market-intelligence system covering win/loss analysis, competitive tracking, customer discovery, and emerging-market research. - Define target markets, analyze segments, and confirm that the segments LegitScript pursues are large enough to support both current and future business. - Determine which distribution channels, including direct, partner, and referral, align with buying preferences in each target segment. - Own the multi-quarter product roadmap as a statement of vision and sequencing, and partner with product management and engineering to translate it into committed delivery plans. - Build business plans and financial models, in collaboration with finance, that give the executive team a clear basis for investment decisions. - Establish pricing, packaging, and distribution strategy for new and existing offerings. - Recommend build, buy, or partner paths for each identified market problem, including the partner profile and terms required to make the path work. - Create the value propositions that differentiate LegitScript in the mind of the buyer relative to competitors. - Partner with product management to hand off validated opportunities with a clear problem definition, target segment, success criteria, and commercial rationale. - Present investment recommendations to the executive team with a clear position and a defensible model behind it. That seems comprehensive. Now Requirements/Qualifications/Skills: The "What You'll Bring" section includes many items. We need to decide how to split. The instruction says use headings for Requirements, Qualifications, Skills. We could put all under Requirements (must-have) and maybe Skills for specific abilities. But we need to avoid filler. Let's parse the "What You'll Bring" paragraph: "10+ years across product strategy, corporate strategy, product management, or business development, including time in B2B SaaS, fintech, regtech, compliance, or trust and safety. Ability to structure an ambiguous commercial question, build the analysis that answers it, and defend the conclusion in front of an executive audience. Direct experience monetizing data, including ownership of a data product sold or licensed externally, whether standing up a new licensed offering or growing an established data feed business. Hands-on data fluency, including comfort running queries against large datasets independently, writing SQL, and working in Python on platforms such as Databricks and Power BI to size datasets, test coverage and field quality, and produce the evidence behind pricing and packaging decisions. Working knowledge of what AI developers and operators of detection systems need from third-party data, including coverage and recall, confidence thresholds, schema and field-level utility, freshness, and delivery by batch export and near real-time API. Written and verbal communication strong enough to carry a business case through executive scrutiny and make a data product understandable to a buyer with no technical background. Experience with financial modeling, including market sizing, pricing analysis, unit economics, and investment cases, in collaboration with finance. Experience negotiating or structuring data licensing and data-sharing agreements, including commercial terms, usage rights, and exclusivity. Experience running structured customer discovery, with the judgment to apply product strategy frameworks rather than follow them mechanically. Enough familiarity with the legal and contractual limits on data licensing, including permitted use, provenance, and privacy, to design products that clear them and to know when counsel is required. Ability to influence across product, engineering, research, sales, and executive stakeholders without formal authority. Preferred Strategy consulting background, ideally at a firm known for analytical rigor and executive-level problem structuring, followed by time operating inside a company. Direct experience driving AI transformation at a software company, including product repositioning, pricing and unit-economics changes, and separating durable AI advantage from table stakes. Domain experience in payments, healthcare, pharmaceuticals, supplements, financial crime, marketplaces, or advertising platforms. Living proximity to Portland, Oregon. We succeed together, care deeply, stay curious, and inspire trust — and we look for those qualities in the people we hire." Now we need to decide which are requirements vs qualifications vs skills. Usually "Requirements" are must-have, "Qualifications" are preferred, "Skills" are abilities. But we can just put all under Requirements and maybe Skills for abilities like SQL, Python, etc. However we need to avoid creating sections with placeholder text. All content is substantive. We could create: - Requirements: the mandatory items (10+ years experience, ability to structure ambiguous commercial question, direct experience monetizing data, hands-on data fluency, working knowledge of AI developers needs, written/verbal communication, experience with financial modeling, experience negotiating data licensing, experience running structured customer discovery, familiarity with legal limits, ability to influence across stakeholders). That seems like a list. - Qualifications: preferred items (Strategy consulting background, direct experience driving AI transformation, domain experience in specific areas, living proximity to Portland, Oregon). Also maybe "We succeed together..." is cultural fit, could be part of Qualifications or omitted? It's not a requirement but a cultural attribute; we could include under Qualifications. - Skills: maybe list specific technical skills: SQL, Python, Databricks, Power BI, data licensing knowledge, financial modeling, etc. But many of those already appear in Requirements. To avoid duplication, we could just have Requirements and Qualifications, and maybe Skills not needed. But instruction says we can use those headings if we have content. We could decide to have Requirements and Qualifications only, and omit Skills if we don't have distinct content. However we have many skill-like items; we could put them under Skills. But then we would duplicate content. Better to follow typical pattern: Requirements = mandatory experience/qualifications; Skills = specific abilities (SQL, Python, etc.); Qualifications = preferred background. Let's attempt to split. First, identify mandatory items (likely those without "Preferred" or "Living proximity" etc). The list before "Preferred Strategy consulting background" seems like requirements. After that, the "Preferred..." etc are qualifications. Thus: Requirements: - 10+ years across product strategy, corporate strategy, product management, or business development, including time in B2B SaaS, fintech, regtech, compliance, or trust and safety. - Ability to structure an ambiguous commercial question, build the analysis that answers it, and defend the conclusion in front of an executive audience. - Direct experience monetizing data, including ownership of a data product sold or licensed externally, whether standing up a new licensed offering or growing an established data feed business. - Hands-on data fluency, including comfort running queries against large datasets independently, writing SQL, and working in Python on platforms such as Databricks and Power BI to size datasets, test coverage and field quality, and produce the evidence behind pricing and packaging decisions. - Working knowledge of what AI developers and operators of detection systems need from third-party data, including coverage and recall, confidence thresholds, schema and field-level utility, freshness, and delivery by batch export and near real-time API. - Written and verbal communication strong enough to carry a business case through executive scrutiny and make a data product understandable to a buyer with no technical background. - Experience with financial modeling, including market sizing, pricing analysis, unit economics, and investment cases, in collaboration with finance. - Experience negotiating or structuring data licensing and data-sharing agreements, including commercial terms, usage rights, and exclusivity. - Experience running structured customer discovery, with the judgment to apply product strategy frameworks rather than follow them mechanically. - Enough familiarity with the legal and contractual limits on data licensing, including permitted use, provenance, and privacy, to design products that clear them and to know when counsel is required. - Ability to influence across product, engineering, research, sales, and executive stakeholders without formal authority. Qualifications (pre