About the Company

At Swiggy, data science and applied machine learning (ML) are integral to our decision-making processes and product development lifecycle. As a Data Scientist, you will collaborate closely with cross-functional teams to develop and deploy end-to-end data-driven products. This includes defining business challenges in mathematical and ML frameworks, iterating on ML/DL methodologies, and deploying solutions to production environments. Our data scientists lead and co-lead numerous initiatives with direct implications for enhancing customer experience and improving key business performance indicators. We champion the open exchange of ideas and encourage both internal knowledge sharing and external publication opportunities.

Job Description

As a Data Scientist, you will collaborate closely with cross-functional teams to develop and deploy end-to-end data-driven products. This includes defining business challenges in mathematical and ML frameworks, iterating on ML/DL methodologies, and deploying solutions to production environments.

Responsibilities

• Utilize your expertise in ML, DL, and statistical techniques to develop innovative ML-based solutions, with a focus on improving the effectiveness of advertisement recommendations. Implement optimization strategies to enhance campaign performance.
• Extract and analyze pertinent information from Swiggy’s extensive historical data to generate insights and formulate solutions to address business and customer experience challenges.
• Work in close collaboration with engineers, product managers, and analysts to establish detailed requirements, develop technical designs, and implement comprehensive inference solutions scalable to Swiggy’s operational demands.
• Stay informed about the latest advancements in ML research related to ad bidding algorithms, recommendation systems, and associated fields, adapting relevant techniques to Swiggy’s unique problem areas.
• Present your work at internal and external venues for both technical and non-technical audiences through publications and presentations.
• Participate in challenging and impactful projects within the logistics domain.
• Collaborate with cross-functional teams, including software developers and product managers, to integrate data-driven solutions into existing systems.
• Develop and deploy advanced machine learning and deep learning models.
• Assume ownership of projects from their initial stages through to final delivery, ensuring high-quality and impactful outcomes.

Qualifications

• Bachelor’s or Master’s degree in a quantitative field, coupled with 0-3 years of industry or research lab experience.
• Essential: Exceptional problem-solving capabilities, encompassing the ability to deconstruct complex issues and develop solutions based on fundamental principles.
• Essential: Demonstrated depth and practical experience in applying ML, DL, and statistical techniques to solve business challenges.
• Preferred: Experience working with large-scale datasets (“big data”) and deploying ML/DL models to production.
• Essential: Strong proficiency in Python, SQL, Spark, and TensorFlow.
• Essential: Excellent verbal and written communication skills.
• Significant Advantage: Experience in the e-commerce and logistics sectors.
• Experience in Generative AI.
• Proven track record of developing and successfully deploying ML and DL data products.
• Experience in Agentic AI, LLMS and NLP.
• Proficiency in Python.

Skills

ATS Keywords

Frequently Asked Questions

Other Information

Experience Level: 0-3 years
Work Arrangement: This is a remote-first position. Employees have the flexibility to work remotely throughout the year. To foster collaboration and team cohesion, employees will convene in their designated base location for one week per quarter.
Equal Opportunity Employer: We are committed to providing equal employment opportunities to all qualified applicants, regardless of race, color, religion, sex, disability status, or any other legally protected characteristic.

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