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Health Data Analytics Director Jobs (NOW HIRING)

Poshmark, Inc

Director, Data Analytics

Redwood City, CA · On-site

Poshmark is seeking a proactive, commercially driven Director of Data Analytics to join the Revenue ... You will define the data architecture for how the Revenue team operates, from inventory health and ...

CYNET SYSTEMS

Public Health Data Analyst

Boston, MA · On-site

$45.84 - $50.84/hr

Conduct epidemiologic surveillance and analysis of healthcare utilization, capacity, workforce, and service delivery data. Monitor syndromic surveillance and other near real-time data sources to ...

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Health Data Analytics Director information

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$71K

$158.1K

$244.5K

How much do health data analytics director jobs pay per year?

As of Sep 11, 2026, the average yearly pay for health data analytics director in the United States is $158,116.00, according to ZipRecruiter salary data. Most workers in this role earn between $112,000.00 and $180,000.00 per year, depending on experience, location, and employer.

What is the difference between Health Data Analytics Director vs Data Scientist?

AspectHealth Data Analytics DirectorData Scientist
Required CredentialsMaster's or PhD in health informatics, data science, or related fields; industry certificationsBachelor's or higher in computer science, statistics, or related fields; often certifications in data analysis
Work EnvironmentHealthcare organizations, hospitals, health tech companiesTech companies, research institutions, healthcare analytics firms
Employer & Industry UsageUsed in healthcare management to lead data initiativesUsed across industries for data modeling and analysis

The Health Data Analytics Director oversees healthcare data strategies and teams, focusing on organizational goals. In contrast, Data Scientists perform detailed data analysis and modeling across various sectors. While both roles require strong analytical skills, the director role emphasizes leadership and healthcare industry expertise.

What cities are hiring for Health Data Analytics Director jobs?

Cities with the most Health Data Analytics Director job openings:

What are popular job titles related to Health Data Analytics Director jobs?

For Health Data Analytics Director jobs, the most frequently searched job titles are:

Director, Data Analytics

Redwood City, CA • On-site

Poshmark, Inc
Apparel and Accessories Stores • 501 - 1,000 employees
Learn more about Poshmark, Incexternal

Full-time

Re-posted 19 days ago

Key responsibilities

  • Build the Revenue Intelligence Infrastructure by defining data needs, connecting data, and creating a single source of truth for demand signals, inventory health, sell-through, and seller GMV opportunity.

  • Own Demand & Supply Intelligence by translating platform signals into a live view of platform health, identifying supply-demand mismatches, and building frameworks to match buyer intent with seller opportunities.

  • Create operational dashboards and decision surfaces for leadership, and lead AI-powered analytics integration to automate demand sensing, campaign performance, and seller opportunity insights.

Job description

About Poshmark
Poshmark is the leading fashion marketplace where style comes alive through discovery, self-expression, and human connection. Powered by a vibrant community of 165 million members, Poshmark brings real people and taste to shopping through a social experience shaped by shared discovery. Buying and selling fashion feels simple, joyful, and personal, while every item tells its own story. Poshmark empowers sellers to grow meaningful businesses, keeps fashion in circulation longer, and gives shoppers access to unique and trusted finds, from everyday pieces to one-of-a-kind vintage and luxury.
Poshmark is seeking a proactive, commercially driven Director of Data Analytics to join the Revenue team. This role is the analytical engine behind Poshmark's merchandising, growth, and supply strategy, responsible for building the intelligence infrastructure that tells us what buyers want, where supply is failing to meet demand, and where seller GMV opportunity is being left on the table.
The ideal candidate doesn't wait to be asked. They see the opportunity in the data before anyone else does, know exactly which signals to pull and how to connect them, and build the dashboards, frameworks, and tools that turn raw platform data into decisions the business can act on in real time.
This is a builder role. You will define the data architecture for how the Revenue team operates, from inventory health and sell-through reporting to trend cycle intelligence, supply gap identification, and seller GMV opportunity and partner directly with the CRO and cross-functional leads across Merchandising, Growth Marketing, Supply Partnerships, Product, and Data Engineering.
Key Responsibilities
  • Build the Revenue Intelligence Infrastructure. Own the end-to-end analytics stack for the Revenue team, defining what data we need, how it connects, and how it surfaces as a single source of truth across demand signals, inventory health, sell-through, and seller GMV opportunity.
  • Own Demand & Supply Intelligence. Translate search acceleration, save behavior, sell-through rates, and category liquidity into a live picture of platform health. Identify where supply is failing to meet demand and build the framework that matches buyer intent to seller opportunity.
  • Drive Trend & Supply Gap Intelligence. Build continuous systems that surface which trends are accelerating, where supply gaps are forming, and where early sourcing is needed, packaging these into actionable briefs that let Supply Partnerships and Merchandising move before a GMV window closes.
  • Create Decision Surfaces, Not Reports. Build operational dashboards for the CRO and Revenue leadership that answer specific business questions daily, and own their ongoing quality, accuracy, and evolution.
  • Lead AI-Powered Analytics. Integrate GenAI tools into daily workflows to accelerate output, and architect toward a Revenue Intelligence Platform where demand sensing, campaign performance, and seller opportunity are surfaced automatically and continuously.
  • Partner Cross-Functionally & Build the Team. Serve as the analytical backbone for Merchandising, Growth, Supply Partnerships, and Product. Partner with Data Engineering to productionize frameworks. Hire, mentor, and grow a team of analysts and promote a data-driven culture across the Revenue org.

What Success Looks Like
In Your First 6 Months
  • Successfully onboard into Poshmark's data environment, Revenue team priorities, and cross-functional workflows.
  • Audit existing analytics infrastructure and deliver a clear assessment of gaps, quick wins, and the roadmap for the Revenue Intelligence build.
  • Stand up core operational dashboards for sell-through, inventory health, and supply gap monitoring actively used by Merchandising and Growth teams.
  • Establish the supply gap brief format and delivery cadence in partnership with the Supply Partnerships team.
  • Build strong cross-functional relationships with Merchandising, Growth, Supply Partnerships, Product, and Data Engineering.
  • Demonstrate proactive intelligence orientation bringing the team signal-backed opportunities they weren't already asking about.

In Your First 12 Months
  • Own and operate a fully functional Revenue Intelligence infrastructure connected, reliable, and used daily across the Revenue team.
  • Deliver a live trend cycle intelligence system that informs editorial, paid media, and supply acquisition decisions on a continuous basis.
  • Build and maintain a supply gap intelligence pipeline that drives measurable Supply Partnerships sourcing activity and new category development.
  • Demonstrate measurable GMV impact through better-timed campaigns, supply gap closures, and demand-driven seller activation.
  • Establish scalable data models, pipelines, and reporting frameworks that reduce manual analytical work across the Revenue team.
  • Begin building toward the AI-powered Revenue Intelligence Platform vision with at least one AI-integrated intelligence layer in production.

Requirements
Experience
  • 8-12 years in data analytics, with meaningful time spent in consumer marketplace, e-commerce, fashion, or retail environments.
  • Proven track record of building analytics infrastructure that changed how a business makes decisions not just reported on decisions already made.
  • Experience working directly with senior commercial leadership and translating business strategy into data architecture.
  • Demonstrated experience leading or growing a team of analysts; strong senior individual contributors will be considered for the right candidate.
  • Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics) or equivalent practical experience.

Technical Skills
  • Expert-level proficiency in SQL. Strong programming skills in Python for data manipulation, statistical analysis, and pipeline automation.
  • Hands-on experience in Databricks, Snowflake, or equivalent large-scale data environments.
  • Experience with dbt or similar data transformation frameworks and modern data stack tooling.
  • Advanced dashboard and visualization skills proficient in Looker, Tableau, or equivalent; knows the difference between a report and a decision surface.
  • Familiarity with behavioral event data, funnel analytics, and supply/demand modeling in a two-sided marketplace context.
  • Practical, hands-on experience using LLMs (e.g., Claude, Gemini, ChatGPT) to write and optimize queries, troubleshoot code, and accelerate analytics workflows.

Commercial & Strategic Skills
  • Commercial instincts to match technical fluency understands how sell-through rate, inventory liquidity, trend velocity, and supply gaps connect to revenue outcomes.
  • Proven ability to translate complex data into actionable business recommendations and communicate effectively with non-technical stakeholders.
  • Strong project management skills; able to manage multiple workstreams across cross-functional partners simultaneously.
  • Ability to tell a story with data and drive executive alignment on analytical findings and infrastructure investment.

Nice to Have
  • Experience with two-sided marketplace data (supply and demand dynamics, inventory liquidity modeling).
  • Background in fashion, resale, or consumer lifestyle platforms.
  • Familiarity with CDPs Segment, mParticle, Hightouch, or Salesforce and behavioral event data pipelines.
  • Experience building or integrating AI/LLM-powered analytics systems or data products.
  • Exposure to paid media performance analytics across Meta, Google, TikTok, and Pinterest.
  • Background in demand forecasting, inventory planning, or assortment analytics.
  • Experience developing or maintaining data governance standards and documentation.
  • Deep understanding of A/B testing methodologies, statistical significance, and causal inference techniques.

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