Description :

- Partner with Product to spot high-leverage ML opportunities tied to business metrics.

- Wrangle large structured and unstructured datasets; build reliable features and data contracts.

Build and ship models to :

- Enhance customer experiences and personalization

- Boost revenue via pricing/discount optimization

- Power user-to-user discovery and ranking (matchmaking at scale)

- Detect and block fraud/risk in real time

- Score conversion/churn/acceptance propensity for targeted actions

- Collaborate with Engineering to productionize via APIs/CI/CD/Docker on AWS.

- Design and run A/B tests with guardrails.

- Build monitoring for model/data drift and business KPIs

Ideal Candidate :

- Strong Data Scientist/Machine Learnings/ AI Engineer Profile

Mandatory (Experience 1) : - Must have 3+ years of hands-on experience as a Data Scientist or Machine Learning Engineer building ML models

Mandatory (Experience 2) : - Must have strong expertise in Python with the ability to implement classical ML algorithms including linear regression, logistic regression, decision trees, gradient boosting, etc.

Mandatory (Experience 3) : - Must have practical hands-on experience with Neural Network / Deep Learning models (TensorFlow / PyTorch preferred)

Mandatory (Experience 4) : - Must have hands-on experience in minimum 2+ usecaseds out of recommendation systems, image data, fraud/risk detection, price modelling, propensity models

Mandatory (Experience 5) : - Must have strong exposure to NLP, including text generation or text classification (Text G), embeddings, similarity models, user profiling, and feature extraction from unstructured text

Mandatory (Experience 6) : - Must have experience productionizing ML models through APIs/CI/CD/Docker and working on AWS or GCP environments

Mandatory (Company) : - Must be from product companies, Avoid candidates from financial domains (e.g., JPMorgan, banks, fintech)

Mandatory (Note) : - The candidate must currently be based in Mumbai or be a native of Mumbai