IMPORTANT NOTE: The work timings for this role are 6:30 pm - 2:30 am IST. Please only apply if you are ready to work in this shift.
Our Purpose
Quartic.ai is a Saa S industrial AI start-up accelerating Industry 4.0 adoption by helping manufacturers unlock more value from existing infrastructure. Our flagship Quartic Platform empowers subject matter experts to build and deploy AI and IIo T applications—without needing programming or data science expertise. Used by Fortune 100 and 500 companies, the platform drives productivity and efficiency in sectors like pharmaceuticals, food & beverage, and CPG, supporting use cases such as process optimization, predictive maintenance, and energy management.
Role
As a Data Scientist, you’ll collaborate across teams to improve the Quartic Platform and develop customized solutions. We’re seeking someone with strong expertise in statistics, machine learning and mathematical optimization to solve real-world industrial challenges.
Data science is central to Quartic’s products and decision-making. We're looking for a candidate who can design and implement advanced statistical models to drive meaningful insights—not just apply pre-built tools. You should have a deep understanding of core algorithms, able to explain why a method works, not just what it does. Whether it's the asymptotic properties behind nonparametric statistics or a specific implementation of partial least squares, you should be comfortable diving into the details. You’ll need to go under the hood—reading through scikit-learn, Py Torch, or XGBoost source code to verify assumptions, trace bugs, or optimize performance. Comfort navigating open-source repos and understanding low-level implementation details is a must.
All About You
Responsibilities:
Develop and implement statistical & machine learning models and algorithms to address business challenges.
Identify, diagnose, and resolve issues in data pipelines, machine learning models, and production systems to ensure seamless operation.
Collaborate with product design and engineering teams to understand data needs and deliver solutions.
Communicate findings to stakeholders through clear and effective data visualizations and reports.
Requirements:
Master’s or Ph D in Statistics, Data Science, Mathematics or a related STEM field.
Deep knowledge of statistical inference, vector calculus, linear algebra and classical machine learning (especially decision trees, PCA, PLS and Bayesian statistics).
3+ years of experience in data science or machine learning environments that requires the combined application of statistical & technical skills
Excellent development skills in Python
Excellent problem-solving skills and the ability to translate complex statistical concepts into practical business applications.
A collaborative team player with hands-on experience in an agile development environment.
Nice to Have:
Experience with convex optimization
Familiarity of Kaggle competitions or similar data science challenges (please provide links to your Kaggle profile or notable competitions).
We are seeking someone with a strong understanding of these technologies and the ability to contribute immediately. If you believe you meet these qualifications, we encourage you to apply!
