Data Scientist

The Data Scientist will lead end-to-end data science projects from data exploration and feature engineering to model deployment and performance monitoring. Responsibilities include developing machine learning, statistical, and predictive models to solve complex Finance Operations challenges, designing and executing experiments and forecasting models, analyzing large datasets using SQL, Python, Spark, and PySpark, collaborating with Product Managers, Data Engineers, and Finance stakeholders, and presenting findings to senior stakeholders. The professional will play a key role in driving data-driven decision-making efforts, ensuring models and pipelines remain scalable, well-documented, and aligned with evolving business priorities. Strong emphasis is placed on model validation, thorough testing, and proactive issue resolution to ensure reliable, high-quality outputs across the organization.

4+ years of experience in Data Science or Applied Machine Learning with strong proficiency in Python and SQL. Hands-on experience building and deploying ML models in production. Solid understanding of statistical modeling and predictive analytics. Experience with Spark/PySpark. Bachelor's in Computer Science, Statistics, Mathematics, Engineering, or related quantitative discipline. B.Tech/B.E. qualification. Familiarity with change management practices and a track record of successful stakeholder engagement across diverse business units is preferred. Prior experience mentoring junior team members and contributing to internal knowledge repositories will also be viewed favorably.