Data Science Manager

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.

2. 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.

3. 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.