Head of Data Science

Landmark Group; Bengaluru; On-site; INR 4,000,000 - 7,000,000; Full time

Job summary

Landmark Group in Bengaluru is seeking a Head of Data Science to architect and scale AI capabilities across geographies, delivering measurable business outcomes. You will lead product, data, AI, and analytics teams to implement pricing optimization, personalization, and forecasting at scale.

Join a fast-paced, high-impact environment where you translate AI innovations into enterprise-grade solutions, establish governance and MLOps practices, and collaborate with senior stakeholders to drive

Qualifications

• 11+ years of applied experience in Data Science / AI / Machine Learning.
• Expertise in pricing optimization, discounts, personalization and demand forecasting.
• Strong programming in Python with PyTorch or TensorFlow; experience with LLMs.

Responsibilities

• Lead end-to-end DS delivery from problem framing to deployment and monitoring.
• Architect and scale production-grade AI capabilities across geographies.
• Design GenAI applications, RAG pipelines, LLM Ops, and governance.

Skills

Data science leadership

Python

ML/AI

MLOps

Transformers/LangChain

Education

Bachelor's in CS/Engineering/Math

Advanced degree preferred

Tools

PyTorch

TensorFlow

LLM platforms

Vector databases

Job description

Our journey started in 1973 with a single store in Bahrain. Since then, we have grown into a global retail and hospitality group. The proud creator of 50 plus value led, own-built brands across retail, hospitality, food, and leisure. Over the years, our UAE-based group has evolved into a comprehensive retail and hospitality entity, with over 2400 retail stores, leisure, and hospitality outlets, spanning the GCC, Middle East, India, Southeast Asia, and Africa.

Landmark Group headquartered in Dubai, UAE is one of GCC's largest omnichannel retailers and India's top home and fashion retailer. We take immense pride in the organic growth of our retail brands, which have blossomed into household names. From Max, Splash, Babyshop, Centrepoint, Shoemart, Home Centre, Emax, Fitness First, to Fun City, to name a few, our brands span across a multitude of categories, enriching the lives of countless families over the past decade.

Csi is a newly established strategic business unit within Landmark Group, bringing together the organization's most critical growth-driving capabilities into one integrated engine. Designed to shape the next phase of retail innovation, Csi unifies Data & Analytics, Loyalty (Shukran), Partnerships & Co-brands, Performance & Digital Marketing, and Customer Product & Martech under one vision. At its core, Csi stands for Customer, Strategy & Intelligence—placing customer experience at the center, enabling smarter business decisions through data, and leveraging AI and Business Intelligence to power every interaction and outcome.

Joining Csi means becoming part of a high-impact team where Product, Data, AI, and Customer Experience converge to build solutions that serve millions of customers across multiple brands. This is an opportunity to work on meaningful business challenges, take ownership of strategic initiatives, and help redefine how modern retail operates in the region. We are looking for individuals who think customer-first, enjoy solving complex problems through data and technology, and are passionate about AI, Martech, Product, or Analytics. If you're looking to contribute to a fast-paced, highly visible environment where your work drive real business impact, Csi offers the opportunity to build the future of customer intelligence on a scale.

We are seeking Head of Data Science who will architect and scale a high-impact, production grade AI capability across geographies. This role is accountable not only for model excellence, but for institutionalizing scientific rigor, engineering discipline, and a culture of experimentation that consistently translates AI into measurable business outcomes.

Operating at the intersection of advanced modeling and executive decision-making, this leader will partner closely with Analytics and business stakeholders to identify, prioritize, and deliver AI initiatives that drive revenue growth, margin expansion, and operational efficiency across Landmark’s retail portfolio.

This role spans core data science applied machine learning, NLP, computer vision, MLOps, and next-generation generative AI systems.

Key Accountabilities:

Strategic & Technical Leadership

• Define and drive the DS / AI roadmap aligned to enterprise priorities for the key brands of Landmark Group.
• Establish modeling standards, experimentation frameworks, code quality benchmarks, and production governance.
• Elevate the technical bar across geographies through structured review mechanisms and architectural oversight.
• Proactively identify high-leverage predictive and optimization opportunities across the retail value chain.

End-to-End DS Delivery

• Design, build, and scale production-grade AI/ML solutions — from problem framing through deployment and iteration.
• Own full lifecycle accountability: data exploration, feature engineering, model development, A/B validation, impact quantification, monitoring, and retraining.
• Lead initiatives in pricing, discount optimization, recommendation systems, personalization, and demand forecasting.
• Drive measurable lift in key business metrics through controlled experimentation.

Generative AI & LLM Systems

• Design and operationalize enterprise-grade GenAI applications.
• Architect LLM-based systems leveraging RAG pipelines, vector databases, knowledge graphs, and orchestration frameworks.
• Develop reusable prompt engineering frameworks and evaluation standards.
• Ensure LLM Ops rigor including model monitoring, guardrails, latency optimization, and governance.
• Stay current with emerging research and frameworks, translating innovation into practical enterprise applications.
• Build scalable, resilient data science APIs with stringent SLA expectations (99%+ availability at high throughput).
• Institutionalize best practices across CI/CD, model versioning, monitoring, retraining, and observability.
• Improve system quality through robust model evaluation and technical benchmarking.

Organizational Leadership

• Coach and develop a passionate team, identifying skill gaps and building structured capability uplift plans.
• Foster a culture of intellectual curiosity, experimentation, and disciplined execution.
• Communicate complex technical developments clearly to senior non-technical stakeholders and executive leadership.
• Collaborate seamlessly across analytics, engineering, product, and business functions.

Qualification & Experience:

• Bachelor’s degree in computer science, Engineering, Mathematics, Statistics, or related technical discipline (advanced degree preferred).
• 11+ years of applied experience in Data Science / AI / Machine Learning.
• Demonstrated expertise in some of the following areas: Pricing optimization and discount modeling Recommendation engines and personalization systems Causal inference, uplift modeling, or price elasticity modeling Optimization techniques (including combinatorial approaches).
• Strong statistical foundation and mastery of modern ML techniques.
• Advanced programming proficiency in Python; hands‑on experience with frameworks such as PyTorch or TensorFlow.
• Experience building and deploying LLM-based applications using enterprise or open‑source models.
• Working knowledge of Transformers, LangChain, LlamaIndex, vector databases, and RAG architecture. Knowledge / Experience on Knowledge Graph RAG.
• Deep understanding of MLOps/LLMOps, experimentation design, and production deployment pipelines.
• Exposure to large‑scale A/B testing systems in online commerce or digital environments and/ OR Experience with algorithms to enable Performance / Growth / Digital marketing; social listening etc.
• Demonstrated ability to translate AI innovation into sustained business impact.

Success Levers:

• AI initiatives directly influencing revenue, margin, and cost efficiency.
• Production systems that are reliable, scalable, and measurable.
• A high-performing data science organization with strong technical standards and clear operating cadence.
• Enterprise adoption of GenAI use cases beyond experimentation into structured value creation.
• Cross-functional trust in the DS function as a strategic partner.