Role Overview:

As a Data Scientist in our Applied ML team, you will sit at the intersection of financial innovation and advanced predictive modeling. You will spend your days architecting sophisticated machine learning pipelines to solve complex problems in credit risk, fraud detection, and personalized financial services. You will collaborate closely with product managers, software engineers, and business stakeholders to translate ambiguous financial data into scalable, production-grade models.

By deploying high-impact algorithms, you will directly influence our core business metrics, ensuring that our financial products are both secure for the organization and seamless for our millions of users.

Key Responsibilities:

- Design and deploy end-to-end machine learning models that optimize credit underwriting processes to reduce default rates and improve approval accuracy.
- Collaborate with cross-functional engineering teams to integrate predictive models into live production environments, ensuring low-latency performance and high reliability.
- Conduct deep-dive exploratory data analysis on large-scale financial datasets to uncover hidden patterns that drive product strategy and business growth.




- Partner with stakeholders to define key performance indicators and translate business requirements into actionable technical roadmaps.
- Automate model monitoring and retraining pipelines to maintain model efficacy in a rapidly evolving fintech landscape.

Required Skillset:

- Demonstrated expertise in building and deploying machine learning models using Python, with a strong grasp of libraries such as Scikit-Learn, XGBoost, LightGBM, or PyTorch.
- Proven ability to write production-quality code and manage data workflows using SQL and cloud-based environments like AWS or GCP.
- Exceptional communication skills, with the ability to distill complex statistical findings into clear, strategic insights for non-technical leadership.
- Strong analytical rigor, typically evidenced by a degree in Computer Science, Statistics, Mathematics, or a related quantitative field from a premier institute.
- High degree of adaptability to thrive in a fast-paced, hybrid work environment across our Bangalore, Hyderabad, or Gurgaon offices, balancing independent research with cooperative team sprints.
- Minimum 2 years and up to 5 years of professional experience in applying machine learning to real-world business challenges.

📌 Data Scientist (India)
🏢 HiringBlaze
📍 India