(IND) STAFF, DATA SCIENTIST (MLE)

About the Team

The Marketplace team serves as a gateway for domestic and international Third-Party sellers. We enable them to manage their entire lifecycle including onboarding, catalogue management, order fulfilment, return & refund processes. Our engineers are responsible for designing, developing, and operating large-scale distributed systems using web/mobile technologies, cloud platforms, big data infrastructure, and AI/ML.

What You Will Do

• Build scalable end-to-end data science solutions for our data products as a Staff Machine Learning Engineer.
• Collaborate with data engineers and analysts to establish ML- and statistics-driven workflows for continuous data quality monitoring.
• Solve complex business problems by scaling advanced machine learning algorithms and statistical models on large datasets.
• Own the MLOps lifecycle: from data monitoring and code refactoring to building robust model monitoring workflows for effective model lifecycle management.
• Demonstrate thought leadership, consulting with stakeholders to build, scale, and deploy holistic ML solutions post-prototyping.
• Promote industry best practices, stay updated on state-of-the-art research, and drive innovation in machine learning applications.

What You Will Bring

• A strong foundation in the principles of machine learning and statistics.
• Experience with web service standards like REST and gRPC patterns.
• Solid experience architecting solutions aligned with Continuous Integration/Continuous Delivery (CI/CD) best practices.
• Familiarity with distributed in-memory computing technologies such as Apache Spark, Hadoop, MapReduce, Hive, and SQL for big data ecosystems.
• Expertise in both supervised and unsupervised machine learning algorithms applied to real-world problems using Python.
• Ability to refactor code and collaborate on developing production-ready ML solutions with full-stack capabilities.
• Skill in creating metrics instrumentation within software components for real-time troubleshooting and performance monitoring.

We seek educational qualifications preferably in Computer Science, Statistics, Engineering or related fields. Strong written and verbal communication skills are essential to present complex ideas clearly across diverse audiences.

Qualifications

Mandatory:
- Option 1: Bachelor's degree in a quantitative field (Statistics, Economics, CS, etc.) with 4 years of analytics experience.
- Option 2: Master's degree in a related field with 2 years of experience.
- Option 3: Alternatively, 6+ years of direct industry experience.

Preferred: Experience in computer vision, forecasting, real-time analytics, or conversational AI assistants is highly valued.