Lead - Data Science

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.