V Mart - Data Science Lead - Machine Learning

Description :

About the job

You will be one of the key leaders in transforming VMart into a truly data-led, people-agnostic organization.

This role goes beyond analytics it is about re-architecting core retail processes, historically dependent on individual judgment, into automated and ultimately autonomous systems.

The vision is to build a colony of digital twins for core processes, capable of making autonomous, data-driven decisions with human-in-the-loop governance.

Responsibilities :

1.Strategic Leadership & Cross-Functional Collaboration

- Partner with Business Heads to identify high-impact opportunities where data science can unlock measurable value.

- Drive alignment between business priorities and technical execution, ensuring data initiatives translate into business outcomes.

- Shape the long-term roadmap for AI adoption and autonomous retail systems.

Hands-On Technical Leadership :

- Architect scalable data science frameworks and reusable accelerators deployable across multiple business units.

- Build proof-of-concepts and foundational models ground-up, setting technical benchmarks and coding standards.

- Lead exploratory data analysis (EDA) to discover actionable insights, anomalies, and opportunities hidden in large-scale retail datasets.

People & Team Development :

- Hire, groom, and develop a high-caliber team of data scientists and ML engineers, instilling ownership and accountability.

- Establish knowledge repositories, coding best practices, and reusable frameworks to accelerate delivery.

- Foster a culture of experimentation, innovation, and technical excellence, while ensuring collaboration across diverse teams.

Requirements :

- Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or related fields.

- At least 5 years of experience in data science, AI, and machine learning, with a minimum of 3 years of experience in leading and managing a team of data scientists, machine learning engineers, and AI specialists.

- Strong proficiency in statistical analysis, machine learning, and AI techniques.

- Hands-on experience with data science, AI, and machine learning tools such as Python, R and SQL.

- Experience with big data technologies such as Hadoop, Spark, and NoSQL databases.

- Strong leadership and communication skills, with the ability to collaborate effectively with cross-functional teams.

- Strong problem-solving and analytical skills, with the ability to think strategically and creatively.

- Strong project management skills, with the ability to manage multiple projects simultaneously