Data Scientist - Machine Learning

Role Overview :

We are looking for a Data Scientist / ML Engineer to build and scale machine learning solutions that directly impact customer experience, revenue growth, and platform intelligence.

You will work closely with Product and Engineering teams to identify high-impact problems, develop ML models, and deploy them into production at scale.

Key Responsibilities :

- Identify and solve high-impact business problems using machine learning in collaboration with Product teams

- Work with large structured and unstructured datasets to build scalable features and data pipelines

- Build and deploy ML models for recommendation systems, ranking, personalization, and matchmaking at scale

- Develop models for pricing optimization, discount strategies, and revenue growth

- Design and implement fraud detection and risk models in real-time systems

- Build propensity models (conversion, churn, acceptance) for targeted decision-making

- Apply NLP techniques including text classification, text generation, embeddings, similarity models, and user profiling

- Develop and train deep learning models using TensorFlow or PyTorch

- Collaborate with engineering teams to productionize ML models using APIs, CI/CD pipelines, and Docker

- Deploy and manage models on AWS or GCP cloud environments

- Design and run A/B experiments to measure model impact with proper guardrails

- Build systems for model monitoring, data drift detection, and performance tracking

Must-Have Skills :

- 3+ years of experience as a Data Scientist / Machine Learning Engineer

- Strong programming skills in Python with hands-on experience in ML libraries

- Solid understanding of machine learning algorithms including regression, classification, decision trees, and boosting techniques

- Hands-on experience with deep learning frameworks (TensorFlow / PyTorch)

- Experience working on at least 2+ use cases such as recommendation systems, NLP, fraud detection, pricing models, or propensity modeling

- Strong exposure to NLP (Natural Language Processing) including embeddings, text classification, similarity models, and unstructured data processing

- Experience in deploying ML models in production using APIs, Docker, CI/CD pipelines

- Hands-on experience with AWS or GCP cloud platforms

- Strong problem-solving and data analysis skills

Good to Have :

i. Experience working in product-based companies (non-financial domain preferred)

ii. Experience in real-time systems and large-scale ML deployments

Important Notes :

Candidates should be currently based in Mumbai or native to Mumbai

Candidates from product companies are preferred

Candidates from pure financial/banking/fintech domains are not preferred

Why Join Us :

- Work on real-world ML problems with direct business impact

- Build systems used at scale across personalization, ranking, and fraud detection

- Opportunity to work with modern ML stack and cloud technologies

- Fast-paced, product-driven engineering culture