Principal Data Scientist

Company Overview:
Care Stack is a complete cloud-based dental software solution for scheduling, clinical, billing, patient engagement, and reporting needs of dental offices of any size – whether it's a single location or a large multi-site DSO with hundreds of locations.
The company was founded in 2015 and the commercial launch was done in early 2018. Since then, more than 1000 offices have chosen Care Stack as their single source of truth. Ours is the fastest growth till date in the dental practice management software market, dominated by 100-year-old distribution companies.

More about Care Stack:
Rated by independent B2B software reviews and research analysts as the most modern, innovative and customer experience focused company in the space with the fastest growth in the segment.
Important strategic go to market partnerships with dental industry leaders like Delta Dental, Darby Dental, and several others.
Venture backed with over USD 60 Million raised till date from leading financial and strategic investors.
Headquartered in Orlando, FL with offices in Minnesota, and Trivandrum.

The Opportunity:

We have a rich and continuously growing pool of product data, and our opportunity is to turn that data into predictive intelligence that can materially improve our customers’ business outcomes.

Our Analytics platform today helps customers understand their business through reporting and visualization. We are now looking to move beyond “what happened” to “what will happen, why, and what should we do about it.”

As a Principal Data Scientist, you will help define and build this capability. You will work across Data Science, Product and R&D to identify high-value problems, formulate hypotheses, experiment with data, build predictive models and turn those learnings into product capabilities.
A key part of the role is to accelerate our R&D and learning loop — making it faster and more rigorous to move from data → hypothesis → experiment → learning → product.

What You Will Drive:
Develop ML and predictive modelling solutions that uncover actionable insights and predictive outcomes from our product data.
Solve complex problems using techniques such as time-series analysis, clustering, causal inference, statistical modelling and machine learning.
Identify opportunities to move our Analytics capabilities beyond reporting towards prediction, recommendations, intelligent alerts and decision support.
Work closely with Product and Engineering to take promising ideas from experimentation to production-grade product capabilities.
Challenge assumptions, design experiments and establish a stronger data-driven R&D and learning culture.
Provide technical leadership and mentor Data Scientists, raising the quality and sophistication of our modelling and analytical practices.
Define and guide the adoption of MLOps best practices to ensure models are robust, scalable, and maintainable in a high-traffic production environment.
Design and lead rigorous experimentation frameworks (A/B testing) to validate the impact of predictive features before and after deployment.

What we are looking for:
10+ years in Data Science, ML, or Predictive Analytics, with a demonstrated history of hands-on technical contributions and product delivery.
Deep expertise in ML, predictive modelling and statistical/analytical methods.
Strong hands-on experience with large-scale product or enterprise datasets.
Ability to leverage data platforms and modern data stacks to build predictive capabilities.
Proven experience taking data science problems from hypothesis and experimentation through modelling and production.
Strong proficiency in Python and SQL.
Experience working closely with Product and Engineering in a SaaS/product environment.
Strong experience…