Overview

Job Title: Analytics Lead – Data, AI & Automation

Responsibilities

• We are looking for a technically strong, hands-on Analytics Lead to build MARS Cosmetics' data intelligence capabilities.
• You will be responsible for organising data across business systems, developing automated data pipelines, integrating AI tools and LLMs, and building Python-based systems that proactively generate actionable business insights.
• Our objective is to move beyond conventional dashboards towards AI-powered, automated and event-driven business intelligence.
• This is a hands-on engineering and analytics role, not a traditional reporting or dashboard management position.
• Data Engineering & Architecture
• Integrate and consolidate data from ERP, marketplaces, Shopify, distributor systems, marketing platforms and internal applications.
• Design and maintain reliable data pipelines, databases and analytical data models.
• Establish data quality, consistency and governance standards.
• Build scalable infrastructure that makes business data easily accessible for analytics and AI applications.
• AI & LLM Integration
• Integrate structured business data with AI tools and LLMs such as OpenAI, Claude and other models through APIs.
• Develop AI-powered analytical workflows that investigate business performance and generate meaningful insights.
• Build natural-language interfaces that allow business teams to query and analyse data.
• Evaluate and implement emerging AI tools to improve analytical capabilities.
• Python Automation & Event-Driven Insights
• Develop Python and SQL-based scripts for automated data processing, analysis and reporting.
• Build systems that proactively detect anomalies, emerging trends and business opportunities.
• Automate root-cause investigations and generate actionable recommendations.
• Create event-driven alerts for situations such as declining SKU sales, unusual inventory movements, margin deterioration and changes in advertising performance.
• Deliver automated insights through email, Teams, dashboards and other business applications.
• Business Intelligence & Analytics
• Develop analytical frameworks covering sales, profitability, marketing, inventory and operations.
• Define standardised KPIs and reusable analytical datasets across business functions.
• Collaborate with business teams to identify high-impact analytical problems and translate them into automated solutions.
• Build dashboards and reporting systems wherever necessary.
• Technical Ownership & Leadership
• Independently design, code, deploy and maintain analytical systems.
• Establish best practices for testing, monitoring, documentation and security.
• Lead and mentor a lean team of data and analytics engineers.
• Prioritise initiatives based on business impact, scalability and execution speed.

Qualifications

• About MARS Cosmetics:
• MARS Cosmetics is a globally recognized beauty brand that thrives on innovation, diversity, and empowering individuals through high-quality beauty solutions. Headquartered in New Delhi, MARS Cosmetics is committed to offering groundbreaking products that meet the ever-evolving needs of consumers worldwide.
• Python: Advanced proficiency in Pandas, data processing, scripting, automation and API integrations.
• SQL & Databases: Strong SQL skills, data modelling and experience with relational databases or data warehouses.
• Data Engineering: Experience building ETL/ELT pipelines and integrating multiple data sources.
• AI/LLMs: Hands-on experience with LLM APIs, function calling, AI agents or AI-powered analytical workflows.
• Analytics: Strong statistical reasoning, anomaly detection and business problem-solving capabilities.
• Automation: Experience developing scheduled and event-driven workflows.
• Engineering: Experience deploying, monitoring and maintaining production-grade solutions.
• A hands-on builder, not just a dashboard developer or analytics manager.
• Has independently built end-to-end data and analytical systems.
• Strong in both technical engineering and commercial problem-solving.
• Comfortable working with fragmented data and converting it into reliable, actionable intelligence.
• Curious, resourceful and capable of independently evaluating new tools and technologies.
• Demonstrates ownership, speed of execution and a preference for simple, scalable solutions.
• Established reliable data pipelines and structured datasets for priority business functions.
• Developed automated systems to detect significant business anomalies and opportunities.
• Integrated analytical workflows with LLMs to generate evidence-backed insights.
• Deployed at least two automated intelligence workflows delivering actionable insights to business stakeholders.
• Opportunity to build an AI-native analytics function from the ground up.
• Work directly on high-impact business problems across multiple functions.
• Significant technical ownership and freedom to evaluate modern technologies.
• Build intelligent systems that influence real business decisions.