Staff Data Scientist, Data Products
for section headings. Use - for any list of duties/requirements/benefits. Use
for prose.
We must preserve all substantive information, not invent or summarize away detail. So we need to keep details like specifics: measurement strategies for core user workflows, define events, metrics, success criteria; partner with engineering to design and validate event instrumentation; conduct deep-dive analyses into feature adoption, workflow completion, user engagement, customer outcomes, operational patterns; build and maintain production-grade dashboards and self-serve reporting in Mixpanel, BigQuery, and BI tooling; translate complex ambiguous usage data into clear prioritized recommendations; define and lead analytical strategies for new compensation and workforce data products; identify high-value opportunities to combine Syndio's aggregated and anonymized first-party data with compensation market data, job-posting and skills data, and other third-party sources; develop diagnostics that measure compensation governance and execution health, including policy-versus-practice gaps, job-architecture health, governance adoption, strategic alignment, and overpayment risk; lead complex initiatives from early exploration and hypothesis formation through analytical validation, productionization, commercialization, and launch; evaluate whether proposed data products are analytically defensible, interpretable, commercially valuable, privacy-preserving, and responsible to use; contribute to give-to-get data strategy; serve as senior analytical partner in product discovery, sprint planning, roadmap discussions, business reviews, product planning cycles; partner with Data Science on experiment design, causal analysis, model evaluation, measurement of model-assisted workflows; work with Customer Success and Sales to connect product usage and data-product insights to customer value, health, renewal risk; establish and champion standards for event data, analytical quality, documentation, interpretability, privacy, responsible data use; provide technical and analytical leadership to other practitioners, raise data literacy, build self-serve capability.
We need to put these under Responsibilities maybe as a list.
About You: 8+ years experience in product analytics, data science, analytics engineering, or closely related role, including substantial experience supporting software products and/or developing analytical products. Proficiency with AI-assisted development tools and workflows, using them to accelerate analysis, prototyping, code generation, documentation, and data-product development while validating outputs and exercising sound judgment. Familiarity with emerging AI and BI innovation — including natural-language interfaces, automated insights, semantic layers, and agentic workflows — and ability to evaluate where these capabilities can improve analytical products and customer experiences. A track record of setting direction and leading complex, cross-functional initiatives with significant product or business impact. Deep proficiency in SQL and strong working proficiency with Python, R, or a comparable analytical language. Advanced knowledge of statistical measurement, benchmarking, experimentation, data modeling, segmentation, data quality assessment, and analytical validation. Experience designing event schemas, product measurement strategies, funnels, dashboards, and self-serve reporting using tools such as Mixpanel, Amplitude, Looker, Tableau, or equivalent. Experience combining large, imperfect datasets into analytically defensible, interpretable, and commercially valuable products or insights. Exceptional judgment and comfort operating in ambiguous, evolving problem spaces; able to determine when approximation is appropriate and when precision is required. Ability to influence senior stakeholders, communicate complex methodologies clearly, and drive alignment across technical and non-technical audiences. Extra Credit: Experience instrumenting or evaluating a GenAI-native product, including model-assisted workflows. Deep familiarity with compensation, pay equity, workforce planning, labor-market data, job architecture, skills taxonomies, or people analytics. Experience with compensation surveys, job-posting data, privacy-preserving analytics, or third-party data licensing and governance. Familiarity with GDPR/CCPA and related privacy considerations for user-level event data and aggregated or anonymized customer data.
We can split: Requirements: 8+ years experience, track record, etc. Qualifications: maybe education not mentioned; we could skip Qualifications if no specific content. Skills: proficiency with SQL, Python/R, AI-assisted tools, etc. Could also list extra credit as separate but maybe under Skills.
Benefits: list items.
Pay: salary range and geo neutral.
We must not include boilerplate like EEO etc. Remove that.
We must not include application instructions or interview overview. So we cut that.
Now produce HTML fragment.
Structure:
About the Role
... maybe a short paragraph summarizing role? The posting has "About The Role We are looking for a Staff Data Scientist, Data Products to serve as a senior analytical and product partner across Syndio's product and data-product portfolio. You will own measurement strategies for our product platform, translate usage and business data into product decisions, and help turn those signals — together with pay-equity, policy, job architecture, market, and workforce data — into customer-facing analytical products. This is a high-autonomy, high-visibility staff role. You will lead ambiguous, cross-functional work from opportunity discovery through methodology, validation, production, and launch; partner with Product, Data Science, Engineering, Privacy, Legal, Sales, and Customer Success; and set standards for analytical rigor, interpretability, data quality, and responsible data use. The role is an individual contributor position with broad influence."
We can keep that as
.
Then Responsibilities:
Responsibilities
- ... each bullet.
We need to break responsibilities into bullet items.
List items:
- Own measurement strategies for Syndio's core user workflows — including offer endorsement, approval, and acceptance — defining events, metrics, and success criteria that guide product decisions.
- Partner with engineering to design and validate event instrumentation for new features, ensuring tracking is accurate, consistent, and privacy-safe from the start.
- Conduct deep-dive analyses into feature adoption, workflow completion, user engagement, customer outcomes, and operational patterns to surface actionable insights.
- Build and maintain production-grade dashboards and self-serve reporting in Mixpanel, BigQuery, and BI tooling that give product teams and senior leaders visibility into product health.
- Translate complex, ambiguous usage data into clear, prioritized recommendations for technical, product, and executive audiences.
- Define and lead analytical strategies for new compensation and workforce data products that make Syndio more valuable, differentiated, and difficult to replicate.
- Identify high-value opportunities to combine Syndio's aggregated and anonymized first-party data with compensation market data, job-posting and skills data, and other third-party sources.
- Develop diagnostics that measure compensation governance and execution health, including policy-versus-practice gaps, job-architecture health, governance adoption, strategic alignment, and overpayment risk.
- Lead complex initiatives from early exploration and hypothesis formation through analytical validation, productionization, commercialization, and launch.
- Evaluate whether proposed data products are analytically defensible, interpretable, commercially valuable, privacy-preserving, and responsible to use.
- Contribute to the give-to-get data strategy by identifying which product and customer signals can strengthen Syndio's broader data assets over time.
- Serve as a senior analytical partner in product discovery, sprint planning, roadmap discussions, business reviews, and product planning cycles.
- Partner with Data Science on experiment design, causal analysis, model evaluation, and measurement of model-assisted workflows.
- Work with Customer Success and Sales to connect product usage and data-product insights to customer value, health, and renewal risk.
- Establish and champion standards for event data, analytical quality, documentation, interpretability, privacy, and responsible data use.
- Provide technical and analytical leadership to other practitioners, raise data literacy across the product organization, and build self-serve capability.
That seems comprehensive.
Now Requirements: maybe
Requirements
- 8+ years of experience in product analytics, data science, analytics engineering, or a closely related role, including substantial experience supporting software products and/or developing analytical products.
- A track record of setting direction and leading complex, cross-functional initiatives with significant product or business impact.
Qualifications: maybe none; we could skip.
Skills: Skills
- Proficiency with AI-assisted development tools and workflows, using them to accelerate analysis, prototyping, code generation, documentation, and data-product development while validating outputs and exercising sound judgment.
- Familiarity with emerging AI and BI innovation — including natural-language interfaces, automated insights, semantic layers, and agentic workflows — and the ability to evaluate where these capabilities can improve analytical products and customer experiences.
- Deep proficiency in SQL and strong working proficiency with Python, R, or a comparable analytical language.
- Advanced knowledge of statistical measurement, benchmarking, experimentation, data modeling, segmentation, data quality assessment, and analytical validation.
- Experience designing event schemas, product measurement strategies, funnels, dashboards, and self-serve reporting using tools such as Mixpanel, Amplitude, Looker, Tableau, or equivalent.
- Experience combining large, imperfect datasets into analytically defensible, interpretable, and commercially valuable products or insights.
- Exceptional judgment and comfort operating in ambiguous, evolving problem spaces; able to determine when approximation is appropriate and when precision is required.
- Ability to influence senior stakeholders, communicate complex methodologies clearly, and drive alignment across technical and non-technical audiences.
- Experience instrumenting or evaluating a GenAI-native product, including model-assisted workflows (extra credit).
- Deep familiarity with compensation, pay equity, workforce planning, labor-market data, job architecture, skills taxonomies, or people analytics (extra credit).
- Experience with compensation surveys, job-posting data, privacy-preserving analytics, or third-party data licensing and governance (extra credit).
- Familiarity with GDPR/CCPA and related privacy considerations for user-level event data and aggregated or anonymized customer data (extra credit).
Benefits: Benefits
- Competitive Compensation: salary targeted at $180,000 - $205,000 per year (see Pay section for details). Actually we might separate Pay. But we can still list benefits like equity, vacation, medical, etc. We'll keep Pay separate.
Benefits list: Syndio Equity, Flexible Vacation Policy (plus paid sick & safe time, compassion leave, voting leave, Paid parental leave), Medical, Dental, Vision (Syndio pays 90% of employee premiums, 50% for dependents), Life Insurance & Disability (full premium covered), 401(k), Fully remote model.
We'll put those as
- .
Pay:
Pay
Target salary range: $180,000 - $2
for prose. We must preserve all substantive information, not invent or summarize away detail. So we need to keep details like specifics: measurement strategies for core user workflows, define events, metrics, success criteria; partner with engineering to design and validate event instrumentation; conduct deep-dive analyses into feature adoption, workflow completion, user engagement, customer outcomes, operational patterns; build and maintain production-grade dashboards and self-serve reporting in Mixpanel, BigQuery, and BI tooling; translate complex ambiguous usage data into clear prioritized recommendations; define and lead analytical strategies for new compensation and workforce data products; identify high-value opportunities to combine Syndio's aggregated and anonymized first-party data with compensation market data, job-posting and skills data, and other third-party sources; develop diagnostics that measure compensation governance and execution health, including policy-versus-practice gaps, job-architecture health, governance adoption, strategic alignment, and overpayment risk; lead complex initiatives from early exploration and hypothesis formation through analytical validation, productionization, commercialization, and launch; evaluate whether proposed data products are analytically defensible, interpretable, commercially valuable, privacy-preserving, and responsible to use; contribute to give-to-get data strategy; serve as senior analytical partner in product discovery, sprint planning, roadmap discussions, business reviews, product planning cycles; partner with Data Science on experiment design, causal analysis, model evaluation, measurement of model-assisted workflows; work with Customer Success and Sales to connect product usage and data-product insights to customer value, health, renewal risk; establish and champion standards for event data, analytical quality, documentation, interpretability, privacy, responsible data use; provide technical and analytical leadership to other practitioners, raise data literacy, build self-serve capability. We need to put these under Responsibilities maybe as a list. About You: 8+ years experience in product analytics, data science, analytics engineering, or closely related role, including substantial experience supporting software products and/or developing analytical products. Proficiency with AI-assisted development tools and workflows, using them to accelerate analysis, prototyping, code generation, documentation, and data-product development while validating outputs and exercising sound judgment. Familiarity with emerging AI and BI innovation — including natural-language interfaces, automated insights, semantic layers, and agentic workflows — and ability to evaluate where these capabilities can improve analytical products and customer experiences. A track record of setting direction and leading complex, cross-functional initiatives with significant product or business impact. Deep proficiency in SQL and strong working proficiency with Python, R, or a comparable analytical language. Advanced knowledge of statistical measurement, benchmarking, experimentation, data modeling, segmentation, data quality assessment, and analytical validation. Experience designing event schemas, product measurement strategies, funnels, dashboards, and self-serve reporting using tools such as Mixpanel, Amplitude, Looker, Tableau, or equivalent. Experience combining large, imperfect datasets into analytically defensible, interpretable, and commercially valuable products or insights. Exceptional judgment and comfort operating in ambiguous, evolving problem spaces; able to determine when approximation is appropriate and when precision is required. Ability to influence senior stakeholders, communicate complex methodologies clearly, and drive alignment across technical and non-technical audiences. Extra Credit: Experience instrumenting or evaluating a GenAI-native product, including model-assisted workflows. Deep familiarity with compensation, pay equity, workforce planning, labor-market data, job architecture, skills taxonomies, or people analytics. Experience with compensation surveys, job-posting data, privacy-preserving analytics, or third-party data licensing and governance. Familiarity with GDPR/CCPA and related privacy considerations for user-level event data and aggregated or anonymized customer data. We can split: Requirements: 8+ years experience, track record, etc. Qualifications: maybe education not mentioned; we could skip Qualifications if no specific content. Skills: proficiency with SQL, Python/R, AI-assisted tools, etc. Could also list extra credit as separate but maybe under Skills. Benefits: list items. Pay: salary range and geo neutral. We must not include boilerplate like EEO etc. Remove that. We must not include application instructions or interview overview. So we cut that. Now produce HTML fragment. Structure:
About the Role
... maybe a short paragraph summarizing role? The posting has "About The Role We are looking for a Staff Data Scientist, Data Products to serve as a senior analytical and product partner across Syndio's product and data-product portfolio. You will own measurement strategies for our product platform, translate usage and business data into product decisions, and help turn those signals — together with pay-equity, policy, job architecture, market, and workforce data — into customer-facing analytical products. This is a high-autonomy, high-visibility staff role. You will lead ambiguous, cross-functional work from opportunity discovery through methodology, validation, production, and launch; partner with Product, Data Science, Engineering, Privacy, Legal, Sales, and Customer Success; and set standards for analytical rigor, interpretability, data quality, and responsible data use. The role is an individual contributor position with broad influence." We can keep that as
. Then Responsibilities:
Responsibilities
- ... each bullet.
We need to break responsibilities into bullet items.
List items:
- Own measurement strategies for Syndio's core user workflows — including offer endorsement, approval, and acceptance — defining events, metrics, and success criteria that guide product decisions.
- Partner with engineering to design and validate event instrumentation for new features, ensuring tracking is accurate, consistent, and privacy-safe from the start.
- Conduct deep-dive analyses into feature adoption, workflow completion, user engagement, customer outcomes, and operational patterns to surface actionable insights.
- Build and maintain production-grade dashboards and self-serve reporting in Mixpanel, BigQuery, and BI tooling that give product teams and senior leaders visibility into product health.
- Translate complex, ambiguous usage data into clear, prioritized recommendations for technical, product, and executive audiences.
- Define and lead analytical strategies for new compensation and workforce data products that make Syndio more valuable, differentiated, and difficult to replicate.
- Identify high-value opportunities to combine Syndio's aggregated and anonymized first-party data with compensation market data, job-posting and skills data, and other third-party sources.
- Develop diagnostics that measure compensation governance and execution health, including policy-versus-practice gaps, job-architecture health, governance adoption, strategic alignment, and overpayment risk.
- Lead complex initiatives from early exploration and hypothesis formation through analytical validation, productionization, commercialization, and launch.
- Evaluate whether proposed data products are analytically defensible, interpretable, commercially valuable, privacy-preserving, and responsible to use.
- Contribute to the give-to-get data strategy by identifying which product and customer signals can strengthen Syndio's broader data assets over time.
- Serve as a senior analytical partner in product discovery, sprint planning, roadmap discussions, business reviews, and product planning cycles.
- Partner with Data Science on experiment design, causal analysis, model evaluation, and measurement of model-assisted workflows.
- Work with Customer Success and Sales to connect product usage and data-product insights to customer value, health, and renewal risk.
- Establish and champion standards for event data, analytical quality, documentation, interpretability, privacy, and responsible data use.
- Provide technical and analytical leadership to other practitioners, raise data literacy across the product organization, and build self-serve capability.
That seems comprehensive.
Now Requirements: maybe
Requirements
- 8+ years of experience in product analytics, data science, analytics engineering, or a closely related role, including substantial experience supporting software products and/or developing analytical products.
- A track record of setting direction and leading complex, cross-functional initiatives with significant product or business impact.
Skills
- Proficiency with AI-assisted development tools and workflows, using them to accelerate analysis, prototyping, code generation, documentation, and data-product development while validating outputs and exercising sound judgment.
- Familiarity with emerging AI and BI innovation — including natural-language interfaces, automated insights, semantic layers, and agentic workflows — and the ability to evaluate where these capabilities can improve analytical products and customer experiences.
- Deep proficiency in SQL and strong working proficiency with Python, R, or a comparable analytical language.
- Advanced knowledge of statistical measurement, benchmarking, experimentation, data modeling, segmentation, data quality assessment, and analytical validation.
- Experience designing event schemas, product measurement strategies, funnels, dashboards, and self-serve reporting using tools such as Mixpanel, Amplitude, Looker, Tableau, or equivalent.
- Experience combining large, imperfect datasets into analytically defensible, interpretable, and commercially valuable products or insights.
- Exceptional judgment and comfort operating in ambiguous, evolving problem spaces; able to determine when approximation is appropriate and when precision is required.
- Ability to influence senior stakeholders, communicate complex methodologies clearly, and drive alignment across technical and non-technical audiences.
- Experience instrumenting or evaluating a GenAI-native product, including model-assisted workflows (extra credit).
- Deep familiarity with compensation, pay equity, workforce planning, labor-market data, job architecture, skills taxonomies, or people analytics (extra credit).
- Experience with compensation surveys, job-posting data, privacy-preserving analytics, or third-party data licensing and governance (extra credit).
- Familiarity with GDPR/CCPA and related privacy considerations for user-level event data and aggregated or anonymized customer data (extra credit).
Benefits
- Competitive Compensation: salary targeted at $180,000 - $205,000 per year (see Pay section for details). Actually we might separate Pay. But we can still list benefits like equity, vacation, medical, etc. We'll keep Pay separate. Benefits list: Syndio Equity, Flexible Vacation Policy (plus paid sick & safe time, compassion leave, voting leave, Paid parental leave), Medical, Dental, Vision (Syndio pays 90% of employee premiums, 50% for dependents), Life Insurance & Disability (full premium covered), 401(k), Fully remote model. We'll put those as
- .
Pay:
Pay
Target salary range: $180,000 - $2