Executive Director, Head of Data Analytics

Executive Director, Head of Data Analytics

About Us

Kardigan is a heart health company working to make cardiovascular disease preventable, curable and no longer the leading cause of death in the world.

It is Kardigan’s mission to develop multiple targeted treatments in parallel that bring people with cardiovascular diseases to the cures they deserve.

Led by Tassos Giannakakos, Jay Edelberg, M.D., Ph.D., and Bob McDowell, Ph.D., Kardigan’s co-founders have reunited after leading Myo Kardia to discover and develop mavacamten, the first cardiac myosin inhibitor, resulting in an acquisition by Bristol Myers Squibb in 2020.

We have a cutting‑edge discovery and translational research platform, a pipeline of late‑stage candidates, and an industry‑leading team that is driven to improve the lives of patients.

At Kardigan, we are motivated by our values which guide how we work, interact, and achieve our goals.
Driven by patients and their families
, we are deeply committed to improving the lives of patients and prioritizing their needs above all else. We believe in being authentic
—leading with truth to bring out the best in others by creating an environment where every person knows they will be fully accepted. With an eagerness to learn
, we encourage the highest levels of curiosity and are open to changing our minds. We are committed to winning as a team with urgency, excellence, and intention, and support each other no matter what role we play or where we sit. Lastly, we strive to enable the impossible because patients are counting on us. We are not afraid to take risks to unlock innovation and advance scientific discoveries.

These values are the foundation of our work, empowering us to make a real difference, every day.

Reports To: VP, Biometrics

Location: Princeton, NJ – On‑site 4 days per week (Mon to Thurs)

The Head of Data Analytics is a strategic leader responsible for the architectural vision and operational execution of data delivery and advanced insights s role reports to the head of Biometrics and unites Statistical Programming and Data Science into a single, cohesive engine. You will build, lead, and develop a high‑performing team, and lead the modernization of our Stats Programming & Data Science infrastructure—bridging traditional SAS‑based regulatory production with R‑based data science—to create real‑time, automated dashboards that accelerate decision‑making across our cardiovascular pipeline.

The Head of Data Analytics serves as a thought‑leader in advanced analytics, ensuring high‑quality, compliant data deliverables while enabling predictive insights, automation, and scalable analytics platforms.

This position will also be responsible for departmental & organizational strategic initiatives.

• Develop the Data Analytics function and strategy aligned with the organizations clinical development goals. Lead the recruitment, on‑boarding, and management of staff and external vendors and consultants
• Ensure data interpretation and statistical analysis support high‑integrity decision making and regulatory submissions
• Partner closely with Biostatistics, Medical, Clinical Operations, Safety, and Regulatory to ensure insights inform decision making and strategy
• Modernization
  
  Roadmap:
  
  Define and execute the strategy to transition from legacy programming silos to a modern, hybrid R/SAS environment.
• Platform Ownership: Lead the design and deployment of an internal analytics platform (e.g., R‑Shiny, Spotfire) to provide cross‑functional teams (Clinical, Safety, Operations) with real‑time, self‑service data review capabilities.
• Regulatory Quality: Oversee the internal team or CRO delivering SDTM, ADaM, and TFLs for regulatory submissions (IND, NDA/MAA).
• Submission Strategy: Develop strategies for electronic submission packages, ensuring “inspection‑readiness” is built into the data pipeline.
• Partner with Biostatistics to ensure alignment between analysis plans, programming execution, and advanced analytics approaches.
• Process Engineering: Drive “Lean Programming” by leveraging automation to reduce turnaround times to support data monitoring activities.
• Standardization: …