Job Summary :

We are seeking a highly skilled and intrinsically curious Data Scientist 3 with 47 years of experience, specifically within the demanding consumer internet (B2C) or large-scale product environment. Based in Mumbai, this role is centered on leveraging massive datasets to fuel product innovation. The Data Scientist will be responsible for end-to-end Machine Learning projects, from developing custom algorithms to deploying and monitoring models that directly enhance customer experiences, boost revenue, and power large-scale user-to-user discovery (matchmaking).

Key Responsibilities :

Product Partnership and Strategy :

- Partner closely with Product teams to proactively identify strategic opportunities where data science and Machine Learning can drive product innovation and measurable business impact.

- Apply statistical chops to find meaningful, actionable insights and hidden trends within large, complex datasets to inform product direction.

Model Development and Application :

- Preprocess massive structured and unstructured datasets (data engineering proficiency) to prepare for modeling and feature engineering.

- Build custom models and advanced algorithms from scratch, applying predictive modeling techniques to solve specific, high-impact business problems, including :

- Enhancing customer experiences (e.g., personalization).

- Boosting revenue (e.g., pricing optimization, churn prediction).

- Powering user-to-user discovery (matchmaking at scale).

- Demonstrate Machine Learning wizardry across critical domains, including recommender systems, Natural Language Processing (NLP), user profiling, image processing, and anomaly detection.

Deployment, Monitoring, and MLOps :

- Collaborate deeply with Engineering teams to successfully deploy models into real-world, low-latency, and high-scale production environments (specifically for matchmaking experiences).

- Build robust tools and processes to continuously monitor model performance (e.g., drift detection, bias checking) and ensure data accuracy post-deployment.

Qualifications :

Experience : Mandatory 36 years of direct experience in Data Science and Machine Learning, with a focus on consumer internet or B2C products.

Education : Degree in Statistics, Computer Science, or Engineering (or relevant formal certification in Data Science).

Technical Stacks (Mandatory) :

- Programming Ninja : Expert-level proficiency in R, Python, and SQL.

- ML Frameworks : Hands-on experience with key libraries including Numpy, Pandas, scikit-learn, Keras, TensorFlow (or similar production-grade frameworks like PyTorch).

- Skills : Strong analytical ability, proven statistical chops in finding meaningful insights in large datasets, and a demonstrably strong problem-solver mindset.

Preferred Skills :

- Visualisation Skills : Proficiency with advanced data visualization tools such as Redshift, Tableau, Looker, or similar BI platforms for communicating results to stakeholders.

- Experience implementing A/B testing frameworks to validate model efficacy and impact on key business metrics.

- Technical familiarity with cloud computing environments (AWS Sagemaker, Google AI Platform) for model training and deployment.

- Prior experience working on high-scale, real-time matchmaking or personalization engines.