Swiggy is hiring for a remote fresher entry level Data Scientist - I job

Position:

Data Scientist - I

Company:

Swiggy

Location:

India

Job Type:

Full-time

Job Mode:

Remote

Job Requisition ID:

N/A

Years of Experience:

0-2 years

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Company Description

• Introduction to Swiggy:
  • Swiggy stands as India's premier on-demand delivery platform.
  • The company embraces a tech-centric approach to logistics and a solution-driven attitude towards consumer needs.
  • Swiggy operates in over 500 cities across India.
• Operations and Reach:
  • The platform collaborates with hundreds of thousands of restaurants.
  • Employs a workforce of more than 5,000 employees.
  • Supported by an independent fleet of over 200,000 Delivery Executives.
• Technological Backbone:
  • Powered by advanced ML technology.
  • Processes terabytes of data daily to ensure seamless and reliable deliveries.
• Growth and Evolution:
  • Originated in 2014 as a hyperlocal food delivery service.
  • Evolved into a logistics powerhouse, excelling in fast and efficient deliveries.
• Expansion and Innovation:
  • Recent additions include Swiggy Instamart, Genie, Dineout, and Minis.
  • Continues to innovate and expand, offering more opportunities for growth.
• Equal Opportunity:
  • Committed to being an equal opportunity employer.
  • Welcomes applications from diverse backgrounds, without discrimination.

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Profile Overview

• Role of a Data Scientist at Swiggy:
  • Integral to decision-making and product development.
  • Collaborates with cross-functional teams.
  • Involves in developing end-to-end data products.
• Responsibilities:
  • Formulating business problems into mathematical/ML models.
  • Iterating on ML/DL methods for production deployment.
  • Contributes to initiatives impacting customer experience and business metrics.
• Team Dynamics:
  • Part of the Ads Monetization Team.
  • Focuses on building and optimizing ML solutions for ads.
  • Manages the lifecycle of ads, including sourcing, pricing, and targeting.
• Skills Utilization:
  • Leverages a strong background in ML/DL/Statistics.
  • Mines and extracts data to ideate business solutions.
  • Collaborates on detailed technical designs and implementation.
• Innovation and Knowledge Sharing:
  • Keeps up with the latest ML research in Ads Bidding and Recommendation Systems.
  • Encouraged to share and publish work internally and externally.

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Qualifications

• Educational Background:
  • Bachelor’s or Master’s degree in a quantitative field.
  • Preferably with 0-2 years of experience in the industry or research labs.
• Essential Skills:
  • Strong problem-solving abilities, capable of deconstructing and formulating solutions from first principles.
  • Depth in applying ML/DL and statistical techniques to business challenges.
• Preferred Experience:
  • Experience working with 'big data.'
  • Proficiency in deploying ML/DL models to production environments.
• Technical Proficiency:
  • Strong knowledge of Python, SQL, Spark, and TensorFlow.
• Communication Skills:
  • Strong written and verbal communication abilities.
• Additional Advantage:
  • Experience in the e-commerce and logistics domain is a significant plus.

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Any Additional Info

• Way of Working:
  • Remote Working: Employees work remotely throughout the year.
  • Quarterly Meetups: Teams gather at their base location for a week once every quarter.
• Data Science at Swiggy:
  • Core to Decision Making: Data Science is crucial for product development and decision-making.
  • Cross-functional Collaboration: Works closely with various teams to develop data-driven solutions.
• Ads Monetization Team:
  • Lifecycle Management: Focuses on the entire ad lifecycle, from sourcing to pricing and targeting.
  • Scalable Solutions: Delivers pragmatic, scalable ML solutions for high-throughput, low-latency systems.
• Role Expectations:
  • ML Solutions Development: Develops next-generation ML solutions to enhance ad recommendations and optimize campaign performance.
  • Data Utilization: Utilizes extensive historical data to identify business solutions.
• Staying Updated:
  • ML Research: Remains informed about the latest ML research and integrates it into Swiggy’s problem-solving approach.
  • Knowledge Sharing: Encouraged to present and discuss work in various forums, both internally and externally.

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