Manager, Data Scientist
Mastercard · Posted Oct 30
Global technology company connecting consumers, financial institutions, merchants, and businesses through secure payment processing and digital commerce solutions
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About the role
The Optimization Solutions team focuses on enhancing digital payment performance across all Mastercard products and regions, analyzing digital performance metrics, identifying factors influencing outcomes, and monitoring broader industry trends to generate actionable, data-driven insights. The team works cross-functionally with external stakeholders to implement optimization solutions across the payments domain. This Manager, Data Scientist role leads the design and technical oversight of advanced analytics and machine learning solutions, building and scaling predictive models and data pipelines for product optimization, growth, and sales enablement.
What you will do
- 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.
Skills used in this role
What the employer is looking for
- 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.
- 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.
- Comfortable working in a fast-paced, deadline-driven environment.
- Effective as both a team player and an individual contributor.
Benefits and support
- Compensation and benefits are detailed in the job posting
About Mastercard
Mastercard is a global technology company in the payments industry that connects consumers, financial institutions, merchants, governments, and businesses worldwide. It operates a fast and secure payment processing network that spans more than 200 countries and territories. Through innovative products and solutions in credit, debit, digital assets, and security, Mastercard makes commerce safer, simpler, and more accessible.
- Industry
- Payments
- Company size
- 10001+ employees
- Founded
- 1966
- Location
- Purchase, New York, USA
- Funding stage
- Public Company
Funding
Public Company · $115M raised
Leadership
Chief Executive Officer
Chief Business Officer
President & Chief Technology Officer
Chief People Officer
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