Data Scientist (Product Company experience only)
OptimHire
- Location
- Navi Mumbai, Maharashtra, India
- Job type
- Full-time
Required skills
- Python
- AWS
- decision trees
- deep learning
- Docker
- fintech
- GCP
- machine learning engineer
- NLP
- propensity models
- regression
- TensorFlow
- Pytorch
About the role
Website:
Job details:
Job Description
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Role & Responsibilities
- 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 2+ 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)
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