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Senior Data Analyst (MedTech)

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Remote from
USA
Salary
USD 175k–200k / yr
Employment
Full Time
Experience
Senior
Published
Apply before
28 Nov 2026
Listing views
28
Application actions
0
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AI Summary

The role, at a glance.

YipitData is seeking a senior, hands-on data analytics leader to own quality, delivery, and expansion of MedTech data products for institutional-investor clients. The role combines advanced analysis of complex healthcare datasets with people leadership, including coaching a team of 3–4 analysts within the first year. Key work includes evaluating claims, prescription, and adjacent healthcare data sources; building validation methodologies; and improving research workflows through automation and AI tools. The successful candidate will translate sector priorities into execution, partner closely with research leadership, and communicate risks, timelines, and strategic recommendations clearly. This is a high-impact player-coach position in a fast-moving, data-intensive environment.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

5/5
RelaxedFast-paced

Autonomy Level

5/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThe role requires senior analytical judgment across messy healthcare data, product development, investor-grade quality standards, and new-source evaluation. It also adds team management and strategic ownership in a high-velocity business environment.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job median (per year)Market rate
$187,500
US market range (per year)$165k–$220k
AI insightThe employer explicitly states an annual USD base-salary range of $175,000–$200,000, with a potential annual performance-based bonus of up to 10% and equity. The midpoint base salary is $187,500 per year. Estimated US market base pay for a senior healthcare/MedTech data analytics leader with team-management responsibilities is approximately $165,000–$220,000 per year.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you evaluate a new claims or prescription dataset for inclusion in a MedTech product?

I would begin by defining the commercial use case and the decisions the dataset must support. I would assess coverage, granularity, timeliness, historical continuity, methodology, licensing constraints, and known biases, then benchmark the data against trusted internal or external reference points. I would document validation results, risks, and a recommendation with a clear path to pilot, scale, or decline.

Describe how you would improve data quality across an established portfolio of research products.

I would first map the full production workflow and identify recurring error types, control gaps, and manual bottlenecks. I would introduce standardized methodology documentation, automated checks for completeness and anomalies, peer-review checkpoints, and measurable quality metrics. I would use root-cause analysis to prioritize the highest-impact fixes and make ownership for each control explicit.

How do you balance being hands-on with data while managing a team of analysts?

I set clear outcome-based ownership for analysts while remaining directly involved in the most ambiguous, high-risk, or strategically important work. Regular one-on-ones, quality reviews, and documented decision frameworks help team members operate independently. My goal is to remove blockers, raise technical standards, and progressively delegate work as capability grows.

How would you explain a complex data-quality limitation to a non-technical research or investment stakeholder?

I would explain the limitation in terms of its practical impact on the decision or metric, rather than technical jargon. For example, I would state what population or behavior may be underrepresented, how large the likely effect is, what conclusions remain reliable, and what mitigation or validation is planned. This keeps the conversation transparent while enabling stakeholders to use the data appropriately.

Give an example of how AI tools can improve an analytics team's workflow without reducing methodological rigor.

AI can accelerate repetitive tasks such as documentation drafting, anomaly triage, data-labeling support, and initial investigation of unexpected changes. I would use it within a controlled workflow where analysts validate outputs, source data remains authoritative, and all material methodology decisions are reviewed by accountable team members. This approach improves speed while preserving auditability and quality standards.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

About Us:

YipitData is the leading market research and analytics firm for the disruptive economy and most recently raised $475M from The Carlyle Group at a valuation of over $1B. Every day, our proprietary technology analyzes billions of alternative data points to uncover actionable insights across sectors like software, AI, cloud, e-commerce, ridesharing, and payments.

Our data and research teams transform raw data into strategic intelligence, delivering accurate, timely, and deeply contextualized analysis that our customers—ranging from the world’s top investment funds to Fortune 500 companies—depend on to drive high-stakes decisions. From sourcing and licensing novel datasets to rigorous analysis and expert narrative framing, our teams ensure clients get not just data, but clarity and confidence.

We operate globally with offices in the US, APAC, and India. Our award-winning, people-centric culture—recognized by Inc. as a Best Workplace for three consecutive years—emphasizes transparency, ownership, and continuous mastery.

What It’s Like to Work at YipitData:

YipitData isn’t a place for coasting—it’s a launchpad for ambitious, impact-driven professionals.

From day one, you’ll take the lead on meaningful work, accelerate your growth, and gain exposure that shapes careers.

Why Top Talent Chooses YipitData:

  • Ownership That Matters: You’ll lead high-impact projects with real business outcomes
  • Rapid Growth: We compress years of learning into months
  • Merit Over Titles: Trust and responsibility are earned through execution, not tenure
  • Velocity with Purpose: We move fast, support each other, and aim high—always with purpose and intention

If your ambition is matched by your work ethic—and you’re hungry for a place where growth, impact, and ownership are the norm—YipitData might be the opportunity you’ve been waiting for.

About the Role:

YipitData’s MedTech business is one of the fastest-growing verticals in the company. We provide institutional investors with differentiated data products covering the medical technology and devices landscape.

The next phase of growth requires us to continue optimizing team performance while embracing new dataset evaluation and buildout – claims data, scripts data, pharma adjacencies, and other healthcare data domains – ultimately aimed at expanding our coverage universe and deepening our competitive moat. At the same time, we’re navigating an intensifying competitive landscape that demands proactive data innovation.

This role is the single biggest unlock for our next stage of growth. We’re looking for someone who can operate as a player-coach — staying close to the data while building and leading a team — to own both the ongoing quality and delivery of MedTech data products and the evaluation and development of new datasets that will fuel the sector’s growth.

As Our Senior Data Analyst (MedTech), You Will:

Team Leadership & Development

  • Manage a team of 3–4 data analysts within your first 6–12 months, with responsibility for coaching and performance management
  • Operate as a player-coach — stay hands-on with the data as needed while delegating operational execution across the team
  • Set clear expectations and provide regular feedback, build a culture of ownership, quality, and accountability
  • Coach team members on effective use of AI agents in their daily workflows, ensure your team is leveraging automation and tooling to maximize impact
  • Develop team members’ technical skills and domain knowledge, create growth paths that align individual development with business needs

Existing Product Ownership & Quality

  • Own overall data quality and accuracy across MedTech research products and analyses – including Research reports, company-level QA, coverage updates, and ad-hoc investigations
  • Review and guide methodology decisions across the team, ensure rigor and consistency in how we process, validate, and deliver data
  • Motivate and organize the team to continually improve data workflows, processing efficiency, and output quality
  • Partner closely with the MedTech Research team as the data team counterpart, ensuring data products align with research priorities and client needs, and launching new coverage where applicable

New Dataset Evaluation & Product Development

  • Identify, scope, and lead evaluations of new data sources — including claims data, prescription data, and adjacent healthcare datasets — assessing commercial viability, data quality, coverage, and fit with our existing product suite
  • Lead Data team in development of methodology and validation frameworks for new data domains, ensuring accuracy and reliability meet institutional investor standards
  • Work with Sector Head to stay current on the healthcare data landscape — new data vendors, evolving regulatory environments, competitive product launches — to identify opportunities before they become obvious

Strategic Contribution

  • Translate sector priorities into team execution — ensure the team is focused on the highest-impact work at any given time
  • Contribute to MedTech roadmap discussions and prioritization, bring a data-informed perspective on what to build next and where the biggest opportunities lie
  • Identify opportunities to improve team workflows and processes, standardize best practices and drive efficiency gains
  • Communicate priorities, timelines, and risks clearly to the Sector Head and cross-functional partners

You Are Likely To Succeed If:

  • 4-8+ years of experience in data analytics, data science, or data product development, with a track record of building data assets in complex, data-intensive domains
  • Strong technical skills mirroring a senior individual contributor (IC) profile:
  • Experience working with large-scale, messy, real-world datasets — you know how to find signal in noise and build robust methodology around imperfect data
  • Healthcare data experience — you’ve worked with healthcare, life sciences, pharma, biotech, or medical device data in a professional context. Deep MedTech expertise is preferred but not required; we value the ability to ramp quickly in a specialized domain.
  • Strong problem-solving and analytical judgment — you can make high-quality decisions in ambiguous situations, prioritize effectively, and know when to go deep vs. when to move fast
  • Clear, direct communication style — you can explain complex data concepts to non-technical stakeholders and advocate for your team’s priorities

Preferred:

  • Prior people management experience — you’ve managed a small team of analysts or data professionals, or you’ve operated as a team lead / senior IC with significant mentorship and project leadership responsibilities
  • Experience in alternative data, financial data products, or investor-facing analytics — you understand what institutional investors need from data and how to build products that meet that bar
  • Demonstrated ability to evaluate and scope new data sources end-to-end — from identifying a potential dataset through assessing quality, coverage, cost, and commercial viability
  • Track record of building new data assets from zero to one — not just maintaining existing systems, but conceiving, validating, and shipping something new
  • Experience with AI/ML tools and workflows — not necessarily building models, but leveraging AI for data processing, quality assurance, or analytical acceleration

Please note that for this position, we are not able to consider candidates who currently or in the future will require visa sponsorship.

Our compensation package includes comprehensive benefits, perks, and a competitive salary:

  • We care about your personal life, and we mean it. We offer flexible work hours, flexible vacation, a generous 401K match, parental leave, team events, wellness budget, learning reimbursement, and more!
  • Your growth at YipitData is determined by the impact that you are making, not by tenure, unnecessary facetime, or office politics. Everyone at YipitData is empowered to learn, self-improve, and master their skills in an environment focused on ownership, respect, and trust. See more on our high-impact, high-opportunity work environment above!
  • Base Salary + Performance-Based Bonus: The annual base salary range for this position is anticipated to be $175,000-$200,000 with eligibility for an annual performance-based bonus of up to 10%. Final compensation may be determined by a number of factors, including, but not limited to, the applicant’s experience, knowledge, skills, abilities, and internal team benchmarks.
  • The compensation package also includes equity.

This role may be performed fully remotely within the United States. Please note that our US headquarters are located in NYC. If the remote work is performed outside of these offices, income may be subject to New York State tax withholding.

We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender, gender identity or expression, or veteran status. We are proud to be an equal opportunity employer.

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