Data Scientist (Product company, Mumbai)

Matchmaking platform

Data Scientist (Product company, Mumbai)

Peak Hire Solutions

Company

Home

Data Scientist (Product company, Mumbai)

at Matchmaking platform

Agency job

via Peak Hire Solutions

2 - 5 yrs

₹15L - ₹28L / yr

Mumbai

Skills

Data Science

Python

Natural Language Processing (NLP)

MySQL

Machine Learning (ML)

Artificial Intelligence (AI)

Algorithms

Logistic regression

Decision trees

Gradient boosting

RESTful APIs

CI/CD

Docker

Amazon Web Services (AWS)

Google Cloud Platform (GCP)

SQL

Amazon Redshift

Looker

Tableau

Storytelling

Review Criteria

Strong Data Scientist/Machine Learnings/ AI Engineer Profile
2+ years of hands-on experience as a Data Scientist or Machine Learning Engineer building ML models
Strong expertise in Python with the ability to implement classical ML algorithms including linear regression, logistic regression, decision trees, gradient boosting, etc.
Hands-on experience in minimum 2+ usecaseds out of recommendation systems, image data, fraud/risk detection, price modelling, propensity models
Strong exposure to NLP, including text generation or text classification (Text G), embeddings, similarity models, user profiling, and feature extraction from unstructured text
Experience productionizing ML models through APIs/CI/CD/Docker and working on AWS or GCP environments
Preferred (Company) – Must be from product companies

Job Specific Criteria

CV Attachment is mandatory
What's your current company?
Which use cases you have hands on experience?
Are you ok for Mumbai location (if candidate is from outside Mumbai)?
Reason for change (if candidate has been in current company for less than 1 year)?
Reason for hike (if greater than 25%)?

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

2–5 years of DS/ML experience in consumer internet / B2C products, with 7–8 models shipped to production end-to-end.
Proven, hands-on success in at least two (preferably 3–4) of the following:
Recommender systems (retrieval + ranking, NDCG/Recall, online lift; bandits a plus)
Fraud/risk detection (severe class imbalance, PR-AUC)
Pricing models (elasticity, demand curves, margin vs. win-rate trade-offs, guardrails/simulation)
Propensity models (payment/churn)
Programming: strong Python and SQL; solid git, Docker, CI/CD.
Cloud and data: experience with AWS or GCP; familiarity with warehouses/dashboards (Redshift/BigQuery, Looker/Tableau).
ML breadth: recommender systems, NLP or user profiling, anomaly detection.
Communication: clear storytelling with data; can align stakeholders and drive decisions.

Review Criteria

Strong Data Scientist/Machine Learnings/ AI Engineer Profile
2+ years of hands-on experience as a Data Scientist or Machine Learning Engineer building ML models
Strong expertise in Python with the ability to implement classical ML algorithms including linear regression, logistic regression, decision trees, gradient boosting, etc.
Hands-on experience in minimum 2+ usecaseds out of recommendation systems, image data, fraud/risk detection, price modelling, propensity models
Strong exposure to NLP, including text generation or text classification (Text G), embeddings, similarity models, user profiling, and feature extraction from unstructured text
Experience productionizing ML models through APIs/CI/CD/Docker and working on AWS or GCP environments
Preferred (Company) – Must be from product companies

Job Specific Criteria

CV Attachment is mandatory
What's your current company?
Which use cases you have hands on experience?
Are you ok for Mumbai location (if candidate is from outside Mumbai)?
Reason for change (if candidate has been in current company for less than 1 year)?
Reason for hike (if greater than 25%)?

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

2–5 years of DS/ML experience in consumer internet / B2C products, with 7–8 models shipped to production end-to-end.
Proven, hands-on success in at least two (preferably 3–4) of the following:
Recommender systems (retrieval + ranking, NDCG/Recall, online lift; bandits a plus)
Fraud/risk detection (severe class imbalance, PR-AUC)
Pricing models (elasticity, demand curves, margin vs. win-rate trade-offs, guardrails/simulation)
Propensity models (payment/churn)
Programming: strong Python and SQL; solid git, Docker, CI/CD.
Cloud and data: experience with AWS or GCP; familiarity with warehouses/dashboards (Redshift/BigQuery, Looker/Tableau).
ML breadth: recommender systems, NLP or user profiling, anomaly detection.
Communication: clear storytelling with data; can align stakeholders and drive decisions.

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