VP, Data & Analytics

New York

Data Engineering

Permanent

Our client is dedicated to enhancing the patient experience in healthcare and is hiring a VP of Data & Analytics to join their team on a remote basis. The successful candidate will lead their data and analytics team, work closely with cross-functional stakeholders and drive innovation in a fast-paced environment.

Responsibilities:

As the VP of Data & Analytics, you will shape and implement the company’s strategic vision for data science, business analytics and data engineering.
You will build strong partnerships with teams across Product, Sales, Marketing, Client Success, and Engineering.
Collaborate with senior leadership to identify business challenges and opportunities, and convert them into actionable, data-driven solutions.
Lead the recruitment, development and retention of a high-performing data and analytics team, ensuring the delivery of crucial insights across various domains.
Partner closely with the SVP, Product to incorporate quantifiable insights into product design and delivery.
Design and manage a scalable data infrastructure strategy to facilitate thorough analysis and reporting across products, ensuring high-quality and reproducible analytics.
Oversee the development and deployment of advanced analytics models and machine learning algorithms to drive growth and meet ambitious goals.
Keep up with industry trends and continuously advance in the data & analytics field, working with large-scale structured and unstructured datasets.

Skillset:

Bachelor’s degree in Computer Science, Statistics, Mathematics or similar.
Over 10 years of leadership experience in analytics, data science or data engineering.
Demonstrated expertise in healthtech.
Proven success in building and leading high-performing data teams, creating a culture of collaboration and accountability.
Extensive knowledge of data governance, security, and compliance best practices, with the ability to balance data accessibility and integrity.
Exceptional communication skills with the ability to translate complex analytical methods for diverse audiences.
Strong interest in analyzing both structured and unstructured data, and deriving strategic insights from quantitative and qualitative research.
Commitment to adhering to organizational information security policies and safeguarding sensitive information in accordance with regulations.