Manager, Data Scientist
Mastercard · Gurugram · Posted 2026-07-18
Tech stack: Python, SQL
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About the role
Manager, Data Scientist About Mastercard: About the Team: The Optimization Solutions team focuses on enhancing digital payment performance across all Mastercard products and regions. As consumer preferences evolve towards digital payments, we prioritize delivering a seamless and secure experience. The team analyses digital performance metrics, identifies factors influencing outcomes, and monitors broader industry trends. We generate actionable, data-driven insights and recommendations, collaborate with external stakeholders to implement optimization solutions, and work cross-functionally to ensure alignment and execution.
Responsibilities:
- As part of the Optimization Solutions team, the role involves:
- Partner with global, cross functional teams to design, develop, and maintain advanced analytics and data science solutions that drive business impact.
- Build, deploy, and scale machine learning models that deliver actionable insights for product optimization, growth, and sales enablement.
- Lead the end to end design and technical oversight of complex data science and ML solutions, ensuring scalability, performance, and engineering excellence.
- Drive the development, validation, monitoring, and continuous improvement of predictive models, statistical techniques, and algorithms aligned with business objectives.
- Establish and uphold best practices across statistical analysis, feature engineering, model evaluation, and performance monitoring.
- Translate advanced analytics, model results, and experimental findings into clear, data driven insights for senior business and product stakeholders.
- Design and implement robust data pipelines, including ingestion, aggregation, and processing of large-scale, high dimensional datasets.
- Research and evaluate emerging AI, machine learning, and data science technologies to identify innovative opportunities and potential risks.
- Contribute to the development and adoption of frameworks, standards, and guardrails that ensure responsible, compliant, and resilient AI solutions.
- Apply appropriate metrics, benchmarking, and measurement frameworks to assess solution effectiveness and business value.
Qualifications:
- Education &
- Strong academic background in Computer Science, Data Science, Technology,
- Mathematics, Statistics, or a related field—or equivalent work experience.
- Experience in data management, mining, analytics, reporting, product development, and quantitative analysis.
- Technical Skills:
- Proficiency in Python, Spark, Hadoop platforms (Hive, Impala, Airflow, NiFi), and SQL.
- Familiarity with machine learning frameworks, libraries, data structures, and software architecture.
- Experience with BI platforms like Tableau or Power BI is a plus.
- Analytical & Communication Skills:
- Strong analytical skills with a proven ability to translate data into compelling insights.
- Experience interacting with stakeholders to understand technical needs and deliver effective solutions.
- Ability to articulate the business value of products and contribute to sales enablement.
- Work Style:
- Comfortable working in a fast-paced, deadline-driven environment.
- Effective as both a team player and an individual contributor.
Qualifications
- Education & Strong academic background in Computer Science, Data Science, Technology
- Mathematics, Statistics, or a related field—or equivalent work experience.
- Experience in data management, mining, analytics, reporting, product development, and quantitative analysis.
- Proficiency in Python, Spark, Hadoop platforms (Hive, Impala, Airflow, NiFi), and SQL.
- Familiarity with machine learning frameworks, libraries, data structures, and software architecture.
- Experience with BI platforms like Tableau or Power BI is a plus.
- Analytical & Communication Skills:
- Strong analytical skills with a proven ability to translate data into compelling insights.
- Experience interacting with stakeholders to understand technical needs and deliver effective solutions.
- Ability to articulate the business value of products and contribute to sales enablement.
- Work Style: Comfortable working in a fast-paced, deadline-driven environment.
- Effective as both a team player and an individual contributor.
Responsibilities
- As part of the Optimization Solutions team, the role involves:
- Partner with global, cross functional teams to
- design, develop, and maintain advanced analytics and data science solutions that drive business impact.
- Build, deploy, and scale machine learning models that deliver actionable insights for product optimization, growth, and sales enablement.
- Lead the end to end design and technical oversight of complex data science and ML solutions, ensuring scalability, performance, and engineering excellence.
- Drive the development, validation, monitoring, and continuous improvement of predictive models, statistical techniques, and algorithms aligned with business objectives.
- Establish and uphold best practices across statistical analysis, feature engineering, model evaluation, and performance monitoring.
- Translate advanced analytics, model results, and experimental findings into clear, data driven insights for senior business and product stakeholders.
- Design and implement robust data pipelines, including ingestion, aggregation, and processing of large-scale, high dimensional datasets.
- Research and evaluate emerging AI, machine learning, and data science technologies to identify innovative opportunities and potential risks.
- Contribute to the development and adoption of frameworks, standards, and guardrails that ensure responsible, compliant, and resilient AI solutions.
- Apply appropriate metrics, benchmarking, and measurement frameworks to assess solution effectiveness and business value.