Job Title: Data Scientist I
Job ID: 19701
Location: Bangalore, Karnataka (Remote – Quarterly in-office)
Employment Type: Full-Time
Batch: Open to all batches (0-3 years of experience)
Experience: 0-3 Years
Salary: As per Industry Standards
Qualification: Bachelor’s or Master’s Degree in a Quantitative Field
Certifications if any: Not mandatory, but relevant ML/AI certifications are a plus
About Us
Swiggy, India’s leading on-demand delivery platform, revolutionizes how consumers access food, groceries, and everyday essentials. With a strong focus on innovation, Swiggy leverages advanced technology and AI to provide seamless and efficient delivery services across India. Our team is powered by data-driven insights and a passion for convenience, making us a household name. As part of our growth journey, our Data Science team plays a pivotal role in shaping the future of customer experience, logistics, and platform intelligence. With a remote-first approach and an emphasis on collaboration, we ensure that our employees thrive in a culture of trust, experimentation, and excellence.
Key Responsibilities
As a Data Scientist I at Swiggy, your work will directly influence key business metrics and customer experience across our platforms. Your primary responsibilities will include:
Develop and implement machine learning (ML) and deep learning (DL) models to enhance ad recommendation systems.
Leverage optimization techniques to improve campaign performance across multiple touchpoints.
Mine and analyze Swiggy’s vast historical data to derive actionable insights.
Collaborate with cross-functional teams including product managers, analysts, and software engineers to deliver data-driven products.
Design and deploy scalable ML inference systems to support real-time business needs.
Keep pace with the latest ML research and apply advancements to solve Swiggy-specific problems.
Present and publish work to both internal stakeholders and external technical audiences.
Drive projects from ideation to production, maintaining high-quality and impactful outcomes.
Develop solutions that support logistics optimization and customer engagement enhancements.
Use data visualization and analytics to communicate insights clearly and effectively.
Required Skills
To be successful in this role, Swiggy expects the following competencies:
Strong problem-solving ability with a first-principles approach to complex challenges.
Hands-on experience with machine learning and deep learning techniques in real-world applications.
Proficiency in Python for building ML pipelines and data analysis.
Expertise in SQL and distributed computing frameworks like Spark.
Experience with TensorFlow or similar frameworks for model development.
Ability to build, train, and deploy ML/DL models at scale.
Strong analytical thinking and statistical knowledge.
Clear and concise written and verbal communication skills.
Passion for building AI products that improve customer experiences.
Commitment to continuous learning and applying cutting-edge methodologies.
Preferred Skills
While not mandatory, the following skills and experiences are advantageous:
Prior experience working with large-scale datasets (“Big Data”) and handling high-volume traffic environments.
Experience deploying ML/DL models into production and monitoring performance.
Exposure to Generative AI, Agentic AI systems, or LLMs.
Understanding of Natural Language Processing (NLP) and applications in real-time systems.
Knowledge of the e-commerce, logistics, or food delivery industry.
Experience contributing to open-source projects or publishing ML research.
Familiarity with cloud platforms (AWS, GCP, Azure) for scalable ML infrastructure.
Enthusiasm for experimentation and quick iteration in a fast-paced startup environment.
Contributions to technical blogs, conferences, or white papers.
Passion for building ethical and responsible AI systems.
Perks & Benefits
Swiggy offers a dynamic and rewarding work environment where your contributions directly impact millions of users. Benefits include:
Remote-first working model with quarterly team meetups at your base location.
Comprehensive health insurance coverage for employees and dependents.
Generous paid time off, parental leave, and wellness breaks.
Performance-based incentives and ESOP opportunities.
Learning and development budgets to support continuous skill growth.
Access to internal knowledge-sharing platforms and mentorship programs.
Inclusive and diverse team culture with a strong emphasis on employee well-being.
Modern technology stack and freedom to experiment with the latest tools.
Exposure to large-scale real-world ML applications.
Collaborative and innovation-driven work culture.
Why Join Us?
Swiggy isn’t just a food delivery company—it’s a data-driven technology powerhouse. Here’s why becoming part of our Data Science team is a game-changer for your career:
Impact at Scale: Your work will touch the lives of millions of users across India and influence core business decisions.
Remote Flexibility: Enjoy a modern, hybrid work culture that values productivity over presence.
Tech-First Environment: Be at the forefront of building cutting-edge ML solutions and deploying them at real-world scale.
Cross-Functional Exposure: Collaborate across engineering, product, and business teams to bring your models to life.
Research to Real-World: Apply academic knowledge to solve practical business problems with end-to-end ownership.
Recognition and Thought Leadership: Get opportunities to publish research, contribute to blogs, and represent Swiggy at top tech conferences.
Learning Culture: We invest in your growth with access to courses, certifications, and technical mentorship.
Mission-Driven Work: Be part of a company redefining how India eats, shops, and lives every day.
At Swiggy, we believe in celebrating diverse perspectives and are committed to creating an inclusive environment where everyone can thrive.
How to Apply
Apply Now: Click Here to Apply
We encourage all qualified candidates, regardless of background, to apply. Swiggy is proud to be an equal opportunity employer committed to building a diverse and inclusive workforce.
