Swiggy Data Scientist Job Openings 2025 | Bangalore 

Qualifications

For Data Scientist —

What qualities are we looking for?

• Bachelors or Masters degree in a quantitative field with 0-3 years of industry/research lab experience
• Required: Excellent problem solving skills, ability to deconstruct and formulate solutions from first-principles
• Required: Depth and hands-on experience in applying ML/DL, statistical techniques to business problems
• Preferred: Experience working with ‘big data’ and shipping ML/DL models to production
• Required: Strong proficiency in Python, SQL, Spark, Tensorflow
• Required: Strong spoken and written communication skills
• Big plus: Experience in the space of ecommerce and logistics
• Experience in Generative AI
• Proven track record of developing and shipping ML and DL data products
• Experience in Agentic AI , LLMS and NLP
• Proficiency in Python

What will you get to do here?

• You will leverage your strong ML/DL/Statistics background to build new and next generation of ML based solutions to improve the quality of ads recommendation and leverage various optimization techniques to improve the campaign performance.
• You will mine and extract relevant information from Swiggy’s massive historical data to help ideate and identify solutions to business and CX problems.
• You will work closely with engineers/PMs/analysts on detailed requirements, technical designs, and implementation of end-to-end inference solutions at Swiggy scale.
• You will stay abreast with the latest in ML research for Ads Bidding algorithms, Recommendation Systems related areas and help adapt it to Swiggy’s problem statements.
• You will publish and talk about your work in internal and external forums to both technical and layman audiences.
• Opportunity to work on challenging and impactful projects in the logistics domain
• Collaborate with cross-functional teams, including software developers and product managers, to integrate data-driven solutions into our systems
• Develop and deploy machine learning and deep learning models
• Take ownership of projects from inception to delivery, ensuring high-quality and impactful results.

For Associate Data Scientist —

What qualities are we looking for?

• Monitoring & Debugging: Familiarity with observability tools (Grafana, Prometheus, Cloud Monitoring).
• Data Systems Knowledge: Hands-on with SQL, Python, Basic Spark
• Statistical Intuition: Ability to distinguish noise vs. genuine anomalies in KPIs.
• Problem-Solving: Strong troubleshooting skills under time pressure.
• Communication: Crisp incident communication and handoff to DS/engineering teams.
• Documentation Discipline: Updating incident logs, playbooks, and IRPs post-mortem.

What will you get to do here?

• Monitoring automated alerts across domains.
• Executing defined incident response runbooks.
• Debugging issues using available RCA tools, observability tools, logs, and dashboards.
• Determining whether the issue is operational or model-related.
• Escalating to the model owner when necessary.
• Ensuring incident reports are logged with root-cause summaries and resolution notes.
• Every domain maintains a structured Incident Response Plan (IRP):
• Alerts – List of metrics and conditions that trigger an incident (e.g., data pipeline delays, sharp metric drops, API errors).
• Response – Step-by-step guide for initial checks (logs, dashboards, health checks).
• Tools to Debug – Domain-specific tools (Grafana, DBR notebooks, feature store dashboards).
• Escalation Triggers – Clear thresholds for escalation to model owners (data quality corruption, unexplained metric deviations).