Manager - Analytics

Ways of working – Employees will come to the office twice or thrice a week at their base location and work remotely for the remaining days.

Tech Lead - Analytics & Data Products

Years of Experience: 6-8 years

About the team & the role:

Founded in 2014, Swiggy is India's leading tech-driven on-demand delivery platform with a vision to elevate the quality of life for the urban consumer by offering unparalleled convenience. The Analytics team at Swiggy partners with decision-makers to solve problems across the value chain while developing data products and solutions that integrate machine learning for driving operational excellence and business impact.

What qualities are we looking for?

• Bachelor’s/Master’s degree in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field.
• 6-8 years of hands-on experience in analytics, data science, or related fields with a focus on data products and ML-driven insights.
• Strong understanding of machine learning techniques (Regression, Classification, etc.) along with practical experience in implementing ML solutions.
• Proven experience in operational excellence, driving streamlined processes and efficiencies across analytics functions.
• Ability to design scalable system-driven solutions and optimize data architecture and pipelines.
• Strong communication and collaboration skills with demonstrated success in leading medium-sized technical teams.
• Experience working with cross-functional teams including data engineering, business, and product teams to improve data product reliability and accuracy.

What will you get to do here?

• Focus on Data Products: Take ownership of designing, developing, and deploying data products to enhance insight generation and improve decision-making capabilities across the organization.
• Machine Learning Integration: Develop ML models for business needs such as classification, prediction, or automation, ensuring they are robust and scalable across different use cases.
• Operational Excellence: Implement strategies for streamlining workflows, increasing team productivity, and ensuring operational efficiency in analytics processes.
• Collaborative Data Engineering: Work closely with the data engineering teams to optimize data pipelines and infrastructure, enhancing accuracy, reliability, and scalability.
• Experimentation and Metrics: Design and measure experiments to test business hypotheses while ensuring the organization has the right metrics frameworks to track progress toward goals.
• Automation & Self-service Platforms: Build user-friendly automated solutions to expedite root cause analyses and empower internal teams with self-service analytics capabilities.
• Leadership & Mentorship: Set high benchmarks for technical execution, lead the team’s roadmap for analytics solutions, and mentor team members for skill-building and impactful delivery.

We are an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, colour, religion, sex, disability status, or any other characteristic protected by the law.