Analytics Lead Data, AI & Automation

Job Title: Analytics Lead – Data, AI & Automation

Location: New Delhi, India

Experience: 5-8 years

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.

About the Role:

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.

Key Responsibilities:

1. 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.

2. 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.

3. 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.

4. 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.

5. 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.

Required Skills:

• 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.

Good to Have: Microsoft Fabric, Azure, Power BI, dbt, workflow orchestration tools, and experience in e-commerce, FMCG or retail.

Ideal Candidate:

• 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.

What Success Looks Like:

Within the first 90 days, you should have:

• 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.

Why Join MARS

• 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.