About SonderMind
At SonderMind, we believe everyone deserves one personalized, connected, and effective mental health destination to take care of their mental health and well-being at any stage of life. SonderMind care encompasses everything from therapy and medication management to meditation and mindfulness exercises. Our clinicians leverage our digital tools and research to deliver increasingly high-quality care and to develop thriving practices. Combining technology and human connection, SonderMind drives better outcomes through our comprehensive approach. Learn more about SonderMind at sondermind.com or download the mobile app, available on iOS and Android. To follow the latest SonderMind news, get to know our clients, and learn about what it’s like to work at SonderMind, you can follow us on Instagram, Linkedin, and Twitter.
About the Role
We are seeking a visionary Director, Applied Science and Data Engineering to lead our AI, Machine Learning (ML), Generative AI initiatives, and Data Engineering. This strategic leadership role requires deep expertise in advanced data science methodologies, large-scale data management, and AI-driven innovation. The ideal candidate will have a proven track record of leading teams in large enterprises and agile startups, preferably with experience in the healthcare and/or the mental health domain.
What you’ll do
- Leadership & Strategy: Develop and execute the company’s AI/ML and data science roadmap, aligning with business goals and driving measurable outcomes.
- AI/ML Innovation: Oversee the design, development, and deployment of cutting-edge AI models, including Generative AI solutions, leveraging extensive data sets for impactful insights.
- Data Strategy: Manage large and complex data ecosystems, ensuring high data quality, governance, and scalability to support AI/ML initiatives.
- Enterprise Data Management: Oversee the Enterprise Data team to design, build, and manage scalable data infrastructure, data pipelines, and data integration frameworks that support AI/ML and business intelligence needs.
- Experience Personalization: Develop and implement AI-driven personalization strategies to enhance user experiences and improve engagement.
- Natural Language Processing (NLP): Lead the development and integration of NLP technologies to extract insights, automate processes, and enhance customer interactions.
- Team Building & Development: Build, mentor, and inspire high-performing data science teams. Foster a culture of innovation, collaboration, and continuous learning.
- Partnerships & Collaboration: Collaborate cross-functionally with engineering, product, and business teams to integrate AI solutions into real-world applications.
- Healthcare/Mental Health Focus: Leverage experience or understanding of healthcare or mental health systems, clinical data, and compliance frameworks to drive AI solutions that improve outcomes and efficiency.
- Research & Advancement: Stay ahead of industry trends, ensuring the adoption of emerging AI technologies and best practices to maintain a competitive edge.
- Operational Excellence: Establish KPIs to measure the success of AI/ML initiatives, driving accountability and impactful results.