Swiggy Data Scientist Job Opening 2024: Remote Opportunities, ML & AI Roles in Ads Monetization
Unlocking Your Career Potential: Join Swiggy as a Data Scientist - I
Are you passionate about data science and eager to work with one of India's leading food delivery platforms? Swiggy is on the lookout for dynamic individuals to join their Ads Monetization Team as a Data Scientist - I. This role offers the unique opportunity to work remotely while solving complex business problems through innovative machine learning (ML) and deep learning (DL) solutions.
About Swiggy
Swiggy, a pioneer in India's food tech industry, has revolutionized the way people order food and groceries. Founded in 2014, Swiggy's mission is to provide unparalleled convenience, offering a seamless experience for customers across India. With products like Swiggy Food and Instamart, Swiggy's success is driven by its cutting-edge technology, efficient operations, and a robust team that continuously pushes boundaries.
Data Science at Swiggy
Data Science and ML are integral to Swiggy’s decision-making and product development processes. At Swiggy, data scientists collaborate closely with cross-functional teams, transforming business challenges into ML models that enhance customer experience and improve operational efficiency. From creating recommendation systems to optimizing user-response models, the role of a data scientist at Swiggy is versatile and impactful.
What You’ll Do as a Data Scientist - I
As part of Swiggy’s Ads Monetization Team, you’ll play a key role in building and optimizing ML solutions across Swiggy’s Food and Instamart business lines. This involves everything from sourcing the right set of ads to personalizing ad targeting. Some key responsibilities include:
- Developing ML-based solutions to improve ad recommendations and boost campaign performance.
- Mining Swiggy’s massive historical data to identify solutions for business problems and customer experience (CX) improvements.
- Collaborating with engineers, product managers, and analysts to design and implement end-to-end inference solutions.
- Staying updated with the latest ML research and adapting innovative algorithms to Swiggy’s specific problem statements.
Qualifications for Success
Swiggy is looking for candidates with a strong background in ML, statistics, and data-driven problem-solving. The ideal candidate should have:
- Educational Background: Bachelor’s or Master’s degree in a quantitative field such as Computer Science, Mathematics, or Data Science.
- Experience: 0-2 years of experience in industry or research labs.
- Skills Required:
- Proficiency in Python, SQL, Spark, TensorFlow.
- Experience with ML/DL techniques and big data.
- Excellent problem-solving skills and the ability to apply solutions from first principles.
- Strong written and verbal communication skills.
Why Swiggy?
Swiggy offers a remote-first work environment, giving employees the freedom to work from anywhere, with quarterly meetups at their base location. For aspiring data scientists, this means the perfect balance of work-life flexibility and professional growth. Working with Swiggy also means being part of a fast-paced, data-driven environment where your contributions have a direct impact on customer experience and business success.
The Future of Ads Monetization
At Swiggy, the Ads Monetization Team is constantly innovating, using ML to optimize ads and enhance user engagement. Ads represent one of the highest throughput systems at Swiggy, and the focus on delivering scalable, pragmatic solutions makes this team an exciting space for data scientists to grow and thrive.
Conclusion
Swiggy’s Data Scientist - I role is perfect for early-career professionals who want to make a mark in data science. If you’re excited by the prospect of working with cutting-edge ML techniques to drive business outcomes, this opportunity could be the career boost you’ve been looking for.
Ready to take the plunge into the world of data science with Swiggy? Apply today and be a part of a company that’s not just a leader in food tech, but a pioneer in data-driven decision-making.
