Data Scientist - Product Based Only (Mumbai)

As a Data Scientist or ML Engineer at this Product Company in Mumbai, your role will involve building and deploying ML models to enhance consumer internet products. You will focus on areas such as recommendation systems, NLP, fraud detection, pricing, and propensity modeling in a dynamic B2C environment. Key Responsibilities: - Develop and productionize ML models end-to-end using Python, including classical algorithms like linear regression, logistic regression, decision trees, and gradient boosting. - Implement use cases in recommender systems, retrieval ranking, NDCG, fraud risk detection, PR-AUC, pricing models, elasticity demand, propensity models, and churn payment. - Apply NLP techniques for text generation, classification, embeddings, similarity models, user profiling, and unstructured text feature extraction. - Deploy models via APIs, Docker, CI/CD pipelines on AWS or GCP. - Collaborate with stakeholders using SQL for data querying, git for version control, and tools like Redshift, BigQuery, Looker, and Tableau for insights. Qualification Required: - 2 years of experience as a Data Scientist or ML Engineer with hands-on model building and at least 7-8 models shipped to production. - Strong expertise in Python for classical ML algorithms. - Experience in at least 2 use cases such as recommenders, image data, fraud risk, pricing, propensity. - Exposure to NLP tasks such as text generation, classification, embeddings, similarity, and user profiling. - Experience in productionizing ML models via APIs, CI/CD, Docker on AWS or GCP. - 2-5 years of experience in consumer internet B2C products is preferred. If there are any additional details about the company in the job description, please provide them for a more comprehensive overview. As a Data Scientist or ML Engineer at this Product Company in Mumbai, your role will involve building and deploying ML models to enhance consumer internet products. You will focus on areas such as recommendation systems, NLP, fraud detection, pricing, and propensity modeling in a dynamic B2C environment. Key Responsibilities: - Develop and productionize ML models end-to-end using Python, including classical algorithms like linear regression, logistic regression, decision trees, and gradient boosting. - Implement use cases in recommender systems, retrieval ranking, NDCG, fraud risk detection, PR-AUC, pricing models, elasticity demand, propensity models, and churn payment. - Apply NLP techniques for text generation, classification, embeddings, similarity models, user profiling, and unstructured text feature extraction. - Deploy models via APIs, Docker, CI/CD pipelines on AWS or GCP. - Collaborate with stakeholders using SQL for data querying, git for version control, and tools like Redshift, BigQuery, Looker, and Tableau for insights. Qualification Required: - 2 years of experience as a Data Scientist or ML Engineer with hands-on model building and at least 7-8 models shipped to production. - Strong expertise in Python for classical ML algorithms. - Experience in at least 2 use cases such as recommenders, image data, fraud risk, pricing, propensity. - Exposure to NLP tasks such as text generation, classification, embeddings, similarity, and user profiling. - Experience in productionizing ML models via APIs, CI/CD, Docker on AWS or GCP. - 2-5 years of experience in consumer internet B2C products is preferred. If there are any additional details about the company in the job description, please provide them for a more comprehensive overview.