Join Our Mission at Sensi.AI
At Sensi.AI, we are dedicated to creating a world where every older adult receives the care they truly deserve. Guided by compassion and driven by innovation, we aim to redefine the future of caregiving. If you’re passionate about making a meaningful impact, join us in advancing Sensi.AI’s virtual assessment tool. This cutting-edge technology monitors seniors' health in their homes 24/7, delivering emergency alerts, actionable insights, and predictive analysis to enable proactive and effective care.
Here, you’ll discover exciting opportunities for professional growth, make a direct and meaningful impact on our products and company, and contribute to a mission that truly matters.
About the role:
As a Senior Data Scientist you will join Sensi's multidisciplinary AI team, composed of data scientists, data analysts and data engineers. This team is responsible for our strategic AI-enabled components dealing with classical and advanced audio signal processing, deep learning techniques, NLP and machine learning.
You will report to the Head of AI and work closely with Product, Business and R&D teams to support across-the-board decision making to execute company business goals.
Responsibilities:
- Be an expert in your domain, drive execution and quality, guide, mentor and collaborate with your team members.
- Be passionate and tech-savvy in data and data science domains with the ability to provide business context and shape data and data pipelines directions.
- Ability to lead research and find solutions for complex problems.
- Taking ownership and being responsible for leading the end-to-end delivery; starting from innovation, experimentation, and development and ending with deployment to production.
- Build culture, trust, and working relationships that enable your team to influence product roadmaps that are driven by customer data.
- Partner and collaborate with product, business data taggers, engineering, and other stakeholders to understand the business to shape Sensi data strategy and AI roadmap and correlate it with business needs.
- Lead continuous improvements in process and tools to drive quality and decision-making. Automate manual processing, CI/CD, MLOps, optimizing data delivery, re-designing infrastructure for better scalability.
- Monitoring models performance in production, continuously working on methods to improve quality and performance
