Data Operations Associate
for section headings: e.g., About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. But we must only include sections when posting has real specific content. We need to map content to these headings appropriately.
We have:
- About Qualitate: description of company. Could be "About the role"? Actually "About Qualitate" is about company, not role. The instruction says use headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we need to map content accordingly.
We have "The Role" description: that's about the role. Could map to "About the role". Or maybe "Responsibilities". The "What You’ll Own" is responsibilities. "Who This Role Is For" is qualifications/requirements. "What Sets You Apart" is preferred qualifications/skills. "Compensation & Benefits" includes Pay and Benefits. "What to Expect" maybe culture, could be omitted or maybe not needed.
We must not repeat job title as heading. No Job ID.
We must not include boilerplate.
We need to preserve all substantive info.
We need to use - for any list of duties/requirements/benefits, and
for prose.
We need to decide sections:
- About the role: could include the paragraph under "The Role" (the description). That's prose.
- Responsibilities: could be the bullet list under "What You’ll Own". That's a list.
- Requirements: could be "Who This Role Is For" (the bullet list of qualifications). That's a list.
- Skills: could be "What Sets You Apart" (list of preferred skills/experience). That's a list.
- Benefits: from "Compensation & Benefits": includes base salary, bonus, equity, benefits, location. Pay and Benefits sections: we need separate Pay and Benefits if present. The posting states base salary range, bonus, equity, benefits (health coverage, flexible PTO, paid holidays), location. So we can have Pay section with salary, bonus, equity. Benefits section with health coverage, flexible PTO, paid holidays, location (maybe location is not benefit but we can include). Or we could combine but instruction: prefer few substantive sections over many thin ones. But we need to include Pay and Benefits only if posting actually states them. It does state compensation and benefits. We could make a single "Compensation & Benefits" section but headings limited to given list: Benefits, Pay, Schedule. We could use Benefits for benefits and Pay for salary/bonus/equity. That seems appropriate.
- Schedule: not mentioned (no schedule info). So we omit Schedule.
- Also we might include "About Qualitate" as maybe not needed; but we could include as a brief intro under maybe "About the role"? But we already have About the role heading for role description. The company description could be placed under a heading like "About Qualitate" but not in allowed headings. The instruction says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings? It says use those for section headings. Likely we should stick to those headings only. So we need to fit company description somewhere, maybe under About the role as part of role description? Could add a brief paragraph about company under About the role before responsibilities. That would preserve info.
Thus:
About the role
Qualitate is building the AI-native continuous intelligence platform for enterprises, investment firms, and asset managers. ... (the whole About Qualitate paragraph). Then maybe also the role description paragraph from "The Role". Could combine.
But we need to preserve all substantive info. So we need to include both company description and role description. Could put them in separate
under same heading.
Then Responsibilities: list from "What You’ll Own". Each bullet as
- .
Then Requirements: list from "Who This Role Is For". Each bullet as
- .
Then Skills: list from "What Sets You Apart". Each bullet as
- .
Then Pay: base salary, bonus, equity. Could be
- Base salary: $100-120K depending on experience.
- Bonus: Eligible for cash bonus tied to individual and company performance.
- Equity: Meaningful early-stage grant with upside tied to company growth.
Then Benefits: health coverage, flexible PTO, paid holidays, location (Full-time, in-person in New York City). Could be - Health coverage
- Flexible PTO
- Paid holidays
- Full-time, in-person in New York City
We should not include "What to Expect" as it's not in allowed headings; but we could maybe omit because not required. However we must preserve ALL substantive information. The "What to Expect" section contains substantive info about culture, excellence, high velocity, etc. If we omit, we lose info. We need to include it somewhere. Could we fit it under a heading like "About the role" or maybe "Benefits"? Not appropriate. Could we create a section not in the list? The instruction says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). The "e.g." suggests those are examples, not exclusive? It says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Likely they expect us to use those headings only. But we need to preserve all substantive info; we could incorporate "What to Expect" into existing sections, maybe under About the role or Benefits? Could add a paragraph under About the role about work environment. That would preserve.
Thus under About the role we can have multiple paragraphs: company description, role description, and work environment (What to Expect). That covers all.
Now ensure we don't repeat job title as heading. No Job ID.
We must not include boilerplate like EEO etc. Not present.
Now produce HTML fragment.
Let's craft:
About the role
Qualitate is building the AI-native continuous intelligence platform for enterprises, investment firms, and asset managers. We automate the entire primary research workflow, from study design and expert recruitment through AI-moderated interviews and insight synthesis, replacing weeks of manual research with high output signal in hours. Primary research remains slow and transactional for everyone involved. Investment and corporate strategy teams spend hundreds of hours coordinating intermediaries, scheduling calls, and synthesizing fragmented insights. Experts face repetitive outreach, screener calls, schedule wrangling, and one-off engagements that offer them little control or lasting value. Qualitate transforms this experience with an AI-native expert network platform that gives participants the flexibility to contribute on their own time while enabling research at unprecedented scale. Qualitate’s AI Moderator conducts thousands of conversations with experts each month, capturing forward-looking purchasing plans, competitive displacement, and real-time ROI signals. Our continuous intelligence platform then turns these conversations into quantified, time-series outputs tracking over 10,000 public and private companies, queryable instantly in natural language. Our customers include some of the world's largest enterprises, hedge funds, PE firms, credit investors, and venture capital firms.
Data is the foundation of everything we build, and as a Data Operations Associate at Qualitate, you'll be part of the core team that keeps that foundation solid. Reporting to the Director of Data Strategy & Operations, you'll sit at the intersection of data quality, process, and tooling – making sure the information flowing through our systems is accurate, reliable, and ready to be trusted by our clients and internal teams. This is a hands-on, high-ownership role. You'll build and refine the pipelines and QA processes that catch problems before they spread, untangle the tricky edge cases, and design the workflows that let us scale without sacrificing quality. You'll have real room to bring your own ideas and grow your technical skills as the team evolves. If you like turning chaos into clean, dependable systems and want to shape how a fast-growing team operates, this is the role for you.
What to Expect Working at Qualitate: Excellence. You'll be held accountable to an exceptionally high bar for quality and impact. High velocity. Fast-paced work environment in terms of growth, decision making, and time to impact. High agency. Ownership over how you work, not just what you work on. We hire people we trust to figure it out. Shared ambition. A small, early team disrupting the multi-billion dollar market research industry with AI. Joy. We work hard and genuinely enjoy working with each other. Dedication to our work is matched only by our passion for fostering an enjoyable, collaborative work environment.
Responsibilities
- Manage data QA processes. Iterate on existing workflows to improve them and create new processes from scratch.
- Handle data escalations. Resolve data errors quickly as they arise, digging into root causes and fulfilling ad-hoc data requests.
- Build compliance guardrails. Bake them into data processes so sensitive information is handled correctly by default.
- Drive end-to-end survey launches, partnering with our Intelligence Strategy & Ops and Market Research teams to deliver on quarterly goals.
- Tackle unstructured data. Develop new approaches for handling it, and build out AI skills and tooling to make the team's work more efficient.
- Manage offshore service provider relationships, developing reporting and tracking tools that improve productivity and keep work aligned with service-level agreements.
- Maintain SOPs. Document and maintain standardized operating procedures, so processes stay consistent and repeatable across the org as we scale.
Requirements
- You have 2+ years in Data Operations or as a QA analyst, with a track record troubleshooting data errors, escalations, and edge cases.
- Data quality is top of mind. You have a strong track record of implementing data validation, cleaning, and quality-assurance processes.
- You're proficient in SQL and Excel/Google Sheets, and you use AI tools to speed up your work.
- You’re detail oriented. Small errors don't slip past you, and you communicate clearly about what you find and how you're resolving it.
- You want real ownership. This is a lean team, so you'll have direct accountability for the systems you build and room to shape how we operate.
- You're comfortable with ambiguity. Early-stage data infrastructure is messy—you're energized by building order out of that, not frustrated by it.
Skills
- You've been early on the data or analytics team at a technology startup and helped build the function from scratch—not just used tools others built.
- You've handled sensitive data, with prior compliance experience identifying and redacting MNPI/PII.
- Exposure to AI/LLM-adjacent data pipelines (labeling, moderation, quality scoring) is a strong plus.
- You've worked in market research, expert networks, or financial services and understand the data integrity bar those industries demand.
- Experience with BI tools (Looker, Tableau, Mode) to build dashboards that non-technical stakeholders actually use.
Pay
- Base salary: $100-120K depending on experience.
- Bonus: Eligible for cash bonus tied to individual and company performance.
- Equity: Meaningful early-stage grant with upside
for prose. We need to decide sections: - About the role: could include the paragraph under "The Role" (the description). That's prose. - Responsibilities: could be the bullet list under "What You’ll Own". That's a list. - Requirements: could be "Who This Role Is For" (the bullet list of qualifications). That's a list. - Skills: could be "What Sets You Apart" (list of preferred skills/experience). That's a list. - Benefits: from "Compensation & Benefits": includes base salary, bonus, equity, benefits, location. Pay and Benefits sections: we need separate Pay and Benefits if present. The posting states base salary range, bonus, equity, benefits (health coverage, flexible PTO, paid holidays), location. So we can have Pay section with salary, bonus, equity. Benefits section with health coverage, flexible PTO, paid holidays, location (maybe location is not benefit but we can include). Or we could combine but instruction: prefer few substantive sections over many thin ones. But we need to include Pay and Benefits only if posting actually states them. It does state compensation and benefits. We could make a single "Compensation & Benefits" section but headings limited to given list: Benefits, Pay, Schedule. We could use Benefits for benefits and Pay for salary/bonus/equity. That seems appropriate. - Schedule: not mentioned (no schedule info). So we omit Schedule. - Also we might include "About Qualitate" as maybe not needed; but we could include as a brief intro under maybe "About the role"? But we already have About the role heading for role description. The company description could be placed under a heading like "About Qualitate" but not in allowed headings. The instruction says use
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It doesn't forbid other headings? It says use those for section headings. Likely we should stick to those headings only. So we need to fit company description somewhere, maybe under About the role as part of role description? Could add a brief paragraph about company under About the role before responsibilities. That would preserve info.
Thus:
About the role
Qualitate is building the AI-native continuous intelligence platform for enterprises, investment firms, and asset managers. ... (the whole About Qualitate paragraph). Then maybe also the role description paragraph from "The Role". Could combine. But we need to preserve all substantive info. So we need to include both company description and role description. Could put them in separate
under same heading. Then Responsibilities: list from "What You’ll Own". Each bullet as
- Base salary: $100-120K depending on experience.
- Bonus: Eligible for cash bonus tied to individual and company performance.
- Equity: Meaningful early-stage grant with upside tied to company growth. Then Benefits: health coverage, flexible PTO, paid holidays, location (Full-time, in-person in New York City). Could be
- Health coverage
- Flexible PTO
- Paid holidays
- Full-time, in-person in New York City We should not include "What to Expect" as it's not in allowed headings; but we could maybe omit because not required. However we must preserve ALL substantive information. The "What to Expect" section contains substantive info about culture, excellence, high velocity, etc. If we omit, we lose info. We need to include it somewhere. Could we fit it under a heading like "About the role" or maybe "Benefits"? Not appropriate. Could we create a section not in the list? The instruction says use
- Manage data QA processes. Iterate on existing workflows to improve them and create new processes from scratch.
- Handle data escalations. Resolve data errors quickly as they arise, digging into root causes and fulfilling ad-hoc data requests.
- Build compliance guardrails. Bake them into data processes so sensitive information is handled correctly by default.
- Drive end-to-end survey launches, partnering with our Intelligence Strategy & Ops and Market Research teams to deliver on quarterly goals.
- Tackle unstructured data. Develop new approaches for handling it, and build out AI skills and tooling to make the team's work more efficient.
- Manage offshore service provider relationships, developing reporting and tracking tools that improve productivity and keep work aligned with service-level agreements.
- Maintain SOPs. Document and maintain standardized operating procedures, so processes stay consistent and repeatable across the org as we scale.
- You have 2+ years in Data Operations or as a QA analyst, with a track record troubleshooting data errors, escalations, and edge cases.
- Data quality is top of mind. You have a strong track record of implementing data validation, cleaning, and quality-assurance processes.
- You're proficient in SQL and Excel/Google Sheets, and you use AI tools to speed up your work.
- You’re detail oriented. Small errors don't slip past you, and you communicate clearly about what you find and how you're resolving it.
- You want real ownership. This is a lean team, so you'll have direct accountability for the systems you build and room to shape how we operate.
- You're comfortable with ambiguity. Early-stage data infrastructure is messy—you're energized by building order out of that, not frustrated by it.
- You've been early on the data or analytics team at a technology startup and helped build the function from scratch—not just used tools others built.
- You've handled sensitive data, with prior compliance experience identifying and redacting MNPI/PII.
- Exposure to AI/LLM-adjacent data pipelines (labeling, moderation, quality scoring) is a strong plus.
- You've worked in market research, expert networks, or financial services and understand the data integrity bar those industries demand.
- Experience with BI tools (Looker, Tableau, Mode) to build dashboards that non-technical stakeholders actually use.
- Base salary: $100-120K depending on experience.
- Bonus: Eligible for cash bonus tied to individual and company performance.
- Equity: Meaningful early-stage grant with upside
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). The "e.g." suggests those are examples, not exclusive? It says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Likely they expect us to use those headings only. But we need to preserve all substantive info; we could incorporate "What to Expect" into existing sections, maybe under About the role or Benefits? Could add a paragraph under About the role about work environment. That would preserve.
Thus under About the role we can have multiple paragraphs: company description, role description, and work environment (What to Expect). That covers all.
Now ensure we don't repeat job title as heading. No Job ID.
We must not include boilerplate like EEO etc. Not present.
Now produce HTML fragment.
Let's craft:
About the role
About the role
Qualitate is building the AI-native continuous intelligence platform for enterprises, investment firms, and asset managers. We automate the entire primary research workflow, from study design and expert recruitment through AI-moderated interviews and insight synthesis, replacing weeks of manual research with high output signal in hours. Primary research remains slow and transactional for everyone involved. Investment and corporate strategy teams spend hundreds of hours coordinating intermediaries, scheduling calls, and synthesizing fragmented insights. Experts face repetitive outreach, screener calls, schedule wrangling, and one-off engagements that offer them little control or lasting value. Qualitate transforms this experience with an AI-native expert network platform that gives participants the flexibility to contribute on their own time while enabling research at unprecedented scale. Qualitate’s AI Moderator conducts thousands of conversations with experts each month, capturing forward-looking purchasing plans, competitive displacement, and real-time ROI signals. Our continuous intelligence platform then turns these conversations into quantified, time-series outputs tracking over 10,000 public and private companies, queryable instantly in natural language. Our customers include some of the world's largest enterprises, hedge funds, PE firms, credit investors, and venture capital firms.
Data is the foundation of everything we build, and as a Data Operations Associate at Qualitate, you'll be part of the core team that keeps that foundation solid. Reporting to the Director of Data Strategy & Operations, you'll sit at the intersection of data quality, process, and tooling – making sure the information flowing through our systems is accurate, reliable, and ready to be trusted by our clients and internal teams. This is a hands-on, high-ownership role. You'll build and refine the pipelines and QA processes that catch problems before they spread, untangle the tricky edge cases, and design the workflows that let us scale without sacrificing quality. You'll have real room to bring your own ideas and grow your technical skills as the team evolves. If you like turning chaos into clean, dependable systems and want to shape how a fast-growing team operates, this is the role for you.
What to Expect Working at Qualitate: Excellence. You'll be held accountable to an exceptionally high bar for quality and impact. High velocity. Fast-paced work environment in terms of growth, decision making, and time to impact. High agency. Ownership over how you work, not just what you work on. We hire people we trust to figure it out. Shared ambition. A small, early team disrupting the multi-billion dollar market research industry with AI. Joy. We work hard and genuinely enjoy working with each other. Dedication to our work is matched only by our passion for fostering an enjoyable, collaborative work environment.