Principal Data Scientist

CareStack; Thiruvananthapuram; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

CareStack is seeking a Principal Data Scientist to drive predictive analytics and ML capabilities across our product. You will partner with Data Science, Product, and R&D to identify high-value problems, formulate hypotheses, and move insights into production-ready features.

You will accelerate our learning loop from data → hypothesis → experiment → learning → product, mentoring junior scientists and defining MLOps standards across a high-traffic platform.

Qualifications

• 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 implementing/building ML lifecycle management and model monitoring loops for product capabilities, rather than just tool familiarity.
• Strong familiarity with ML lifecycle management and model monitoring tools (e.g., MLflow, SageMaker) and strategies for continuous model training and monitoring.
• A proven track record of partnering with product leadership to quantify the business ROI of data science initiatives.
• Strong technical mentoring capability and the ability to influence beyond your immediate team.

Responsibilities

• Develop ML and predictive modelling solutions that uncover actionable insights and predictive outcomes from our product data.
• Solve complex problems using 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.

Skills

Python

SQL

ML/Predictive analytics

Leadership

Experimentation

Tools

MLflow

SageMaker

A/B testing frameworks

Job description

Company Overview:

CareStack 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.

More about CareStack:

• 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 implementing/building ML lifecycle management and model monitoring loops for product capabilities, rather than just tool familiarity.
• Strong familiarity with ML lifecycle management and model monitoring tools (e.g., MLflow, SageMaker) and strategies for continuous model training and monitoring.
• A proven track record of partnering with product leadership to quantify the business ROI of data science initiatives.
• Strong technical mentoring capability and the ability to influence beyond your immediate team.

This Role Is For You If…

• You enjoy finding the signal in large, complex datasets, are deeply curious about what the data can tell us that we don't yet know, and want to turn those discoveries into capabilities that customers can actually use.
• This is a Data Science leadership role - not a Data Architecture role. The core of the role is ML, predictive intelligence and using data to accelerate product learning and create measurable customer value.

Nice to Haves

Experience building ethical and transparent AI/ML systems, with a focus on data privacy and bias mitigation.

Location

Trivandrum

Join us online for future opportunities

Website: https://carestack.com/

Instagram: https://www.instagram.com/carestack.people

LinkedIn: https://www.linkedin.com/company/carestack/mycompany/

Note:

As part of our interview process, we conduct an initial shortlisting to identify candidates who closely match our requirements. While we strive to notify all applicants about their status, if you do not receive a response from us, please understand that your profile has not been shortlisted at this time.