Data Scientist II

Mastercard Inc.; Bogotá ciudad; Presencial; COP 198.715.000 - 331.192.000; Jornada completa

Descripción de la vacante

Mastercard Inc. is seeking a Data Scientist II to advance pricing and interchange strategies through data-driven insights.

You will work across global teams to build predictive models, optimize revenue, and deliver scalable analytics using cloud platforms and modern data architectures. The role emphasizes collaboration with Pricing, Strategy, Finance, Product, and Tech teams, turning complex data into actionable business recommendations and enabling data-driven decisions in a fast-paced

Formación

• Experience with data science, analytics, BI, or related field.
• Strong SQL, data manipulation, and data storytelling skills.
• Proficiency in Python and analytics libraries; familiarity with cloud platforms.

Responsabilidades

• Develop analytics and predictive models supporting pricing, interchange, and commercial strategy.
• Conduct profitability, segmentation, forecasting, simulations, and revenue analyses.
• Design and maintain reporting, dashboards, and self-service analytics.
• Build data pipelines and scalable data products using modern cloud and big data technologies.
• Apply ML methods to uncover trends and opportunities for business decisions.
• Translate business requirements into analytical frameworks and actionable recommendations.

Conocimientos

SQL

Python

Data Visualization

Machine Learning

Statistics

Educación

Bachelor's degree

Master's degree

Herramientas

Databricks

Snowflake

Tableau

Power BI

Airflow

Hadoop

Descripción del empleo

Our Purpose Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Title and Summary Data Scientist II

Our Purpose: Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re helping build a sustainable economy where everyone can prosper. We support a wide range of digital payments choices, making transactions secure, simple, smart and accessible. Our technology and innovation, partnerships and networks combine to deliver a unique set of products and services that help people, businesses and governments realize their greatest potential.

Job Title: Data Scientist II

Overview:

The Global Pricing & Interchange (P&IC) team plays a critical role in shaping Mastercard’s economics strategy and enabling profitable growth across products, services, and markets. The team partners with regional and global business units to execute pricing and interchange strategies under a consistent global framework while driving revenue optimization, commercial simplification, enhanced customer experiences, and strategic transformation initiatives. As a Data Scientist, you will leverage advanced analytics, data science, machine learning, and modern data platforms to transform data into actionable insights that influence strategic business decisions. You will work at the intersection of strategy, analytics, technology, and commercial execution, helping answer complex business questions, identify growth opportunities, improve operational efficiency, and support Mastercard’s long-term pricing and interchange strategy.

Role:

The Data Scientist is responsible for designing and delivering scalable, data-driven solutions that support Pricing & Interchange strategy, business performance optimization, and enterprise decision-making.

Key Responsibilities

• Develop analytics, predictive models, and data science solutions that support pricing, interchange, and commercial strategy initiatives.
• Conduct analyses including profitability assessments, customer and product segmentation, forecasting, simulations, optimization, and revenue analytics.
• Design, develop, and maintain reporting, dashboards, data visualizations, and self-service analytical capabilities supporting global business needs.
• Build and enhance data pipelines, analytical datasets and scalable data products using modern cloud and big data technologies.
• Apply statistical methods, machine learning techniques, and AI-driven approaches to uncover trends, identify opportunities, and solve business challenges.
• Translate business requirements into analytical frameworks and actionable recommendations.
• Partner with Pricing, Strategy, Finance, Product, Technology, and Regional teams to develop insights that support key commercial decisions.
• Present analytical findings and recommendations in a clear, concise, and business-friendly manner.
• Contribute to continuous improvement of data science methodologies, automation opportunities, and analytics capabilities across the organization.

All About You:

• 1–3 years of experience in data science, analytics, business intelligence, quantitative analysis, or a related field.
• Strong understanding of data management, data analysis, statistics, and reporting concepts.
• Proficiency in SQL with experience querying and analyzing large datasets.
• Experience with Python and familiarity with analytics libraries and data science toolsets.
• Experience working with Hadoop/Cloudera, Snowflake, Databricks, Azure/AWS cloud platforms, Microsoft Fabric, SQL Server, and related technologies.
• Experience building and maintaining data pipelines and transformation frameworks using tools such as Databricks, Alteryx, SSIS, or similar platforms.
• Proficiency in data visualization tools such as Power BI and Tableau.
• Experience with workflow orchestration and scheduling tools such as Apache Airflow, NiFi, or equivalent technologies.
• Experience developing machine learning models, predictive analytics solutions, and statistical models.
• Ability to translate complex data and quantitative analyses into actionable business insights and strategic recommendations
• Effective verbal and written communication skills, with the ability to present insights to both technical and non-technical audiences.
• Intellectual curiosity, problem-solving mindset, and passion for using data to solve business challenges.
• Payments, financial services, fintech, pricing, or commercial analytics experience is highly desirable.
• Bachelor’s degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Economics, Finance, or a related field required; Master’s degree is a plus.
• Experience with Generative AI, machine learning deployment, APIs, optimization models, and modern AI/ML platforms is a strong plus.

Corporate Security Responsibility

• All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must.
• Abide by Mastercard’s security policies and practices.
• Ensure the confidentiality and integrity of the information being accessed.
• Report any suspected information security violation or breach, and
• Complete all periodic mandatory security trainings in accordance with Mastercard’s guidelines.

Corporate Security Responsibility

• All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must: Abide by Mastercard’s security policies and practices; Ensure the confidentiality and integrity of the information being accessed; Report any suspected information security violation and

Everyone wants easier ways to pay; we invent them. Checkout lines are slow; we speed them along. Merchants want more sales; we give them data and insights. People need financial access; we connect them. Corporate purchasing is complicated; we make it simple. Commuters are busy; we speed them on their way. Governments need greater efficiencies; we help create them. Small businesses are virtual; we give them access to a world of buyers. Retailers want to fight fraud; we provide the tools.