Senior Data Scientist, Product Data & Analytics

Mastercard is seeking a Senior Data Scientist to join their Product Data & Analytics team, focusing on building internal analytic partnerships and strengthening business health analysis. This role is part of a hands-on global team that provides scalable end-to-end data solutions by working closely with the business.

The position involves developing innovative analytical solutions using advanced machine learning techniques and big data technologies. You'll be responsible for creating predictive models, behavioral segmentation frameworks, and profitability analyses while working with large-scale data sets. The role requires expertise in both classical and deep learning algorithms, along with strong programming skills in Python and experience with big data platforms.

As a Senior Data Scientist, you'll collaborate with global teams to architect and maintain advanced reporting and data visualization capabilities. You'll be expected to translate stakeholder needs into technical analyses and derive actionable insights from complex data sets. The role also includes mentoring junior colleagues and contributing to talent development through technical training and peer review.

The ideal candidate brings 6-8 years of experience in data analytics and quantitative analysis, with strong SQL skills and experience working with big data technologies like Hadoop, Spark, and cloud platforms. You should be comfortable with data visualization tools and have experience in automating data pipelines. Financial institution or payments experience is a plus.

This is an excellent opportunity to join a leading global financial technology company that powers economies and empowers people in over 200 countries. You'll be part of a team that influences decisions across Mastercard through data-driven insights, working on projects that have significant business impact. The role offers the chance to work with cutting-edge technologies while solving complex analytical challenges in the payments industry.