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Recognizable consumer brand, popular ML role and metro hiring produce moderate applicant density.
Requires Consumer Internet/B2C experience and production ML model delivery, limiting cross-industry transferability.
Explicit 1–3 years, mandatory production ML experience and tech stack make filters strict.
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Partner with Product teams to identify and implement high-impact ML opportunities aligned with business goals.
Engineer scalable data pipelines and build, train, and deploy ML models for recommendation, pricing optimization, fraud detection, and user behavior prediction.
Collaborate with Engineering to productionize models using APIs, Docker, CI/CD, AWS; design and analyze A/B experiments; monitor model and business performance continuously.
1-3 years experience in Data Science/Machine Learning within Consumer Internet or B2C Product companies.
Proven experience deploying 4–5 ML models end-to-end in production.
Proficiency in Python, SQL, Git, Docker, CI/CD; experience with AWS/GCP, Redshift/BigQuery, Looker/Tableau.
Work Experience Required: 1-3 years in relevant field.
Experienced in building ML models for recommendation systems, fraud detection, pricing optimization, and churn prediction.
Skilled at translating complex data insights into business impact and influencing stakeholders.
Comfortable working in cross-functional teams including Product and Engineering, owning end-to-end ML solutions at scale.