Mastercard
Financial Services
DataScientistII
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Scientist II at Mastercard. Skills: Data Science, Data Analytics, Machine Learning, Business Intelligence. Architect advanced reporting. Develop advanced reporting”
Industry & Context.
Problem solving; Quantitative skills; Analytical skills; Analytical thinking
What They're Looking For.
Must Have
Bachelor's Degree in Computer Science, Advanced SQL skills, Experience in data management, Experience in data mining, Experience in data analytics, Experience in data reporting, Experience in data product development, Experience in quantitative analysis
Nice to Have
Financial Institution experience a plus, Payments experience a plus, Experience with Python a plus, Experience with R a plus, Experience with SSIS a plus, Experience with SSAS a plus, Experience with SSRS a plus
What You'll Do.
Architect advanced reporting
Develop advanced reporting
Maintain advanced reporting
Develop data visualization capabilities
Maintain data visualization capabilities
Obtain data from multiple sources
Triangulate information
Develop reliable fact bases
Manipulate large-scale databases
Synthesize data insights
Execute cross-functional projects
Build reporting systems
Develop reporting systems
Maintain reporting systems
Build performance metrics
Develop performance metrics
Maintain performance metrics
Extract intellectual capital
Provide 1st level insights
Provide 1st level conclusions
Provide 1st level assessments
Apply quality control
Apply data validation
Apply cleansing processes
Lead junior team members
Mentor junior team members
Guide junior team members
Communicate business impacts
Interact with management
Interact with internal stakeholders
How You'll Work.
Team & Collaboration
Global teams; Regional teams; Cross-functional projects; Leadership stakeholders; Technology stakeholders; Sales stakeholders; Marketing stakeholders; Product teams
Communication Scope
Present findings; Communicate results; Communicate business impacts; Oral communication; Written communication
Full Job Description
**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 ### Job Description Product Data & Analytics Team Data Scientist II – Product Data & Analytics Overview Product Data & Analytics team builds internal analytic partnerships, strengthening focus on the health of the business, portfolio and revenue optimization opportunities, initiative tracking, new product development and Go-To Market strategies. • Are you excited about Data Assets and the value they brings to an organization? • Are you an evangelist for data driven decision making? • Are you motivated to be part of a Global Analytics team that builds large scale Analytical Capabilities supporting end users across 6 continents? • Do you want to be the go-to resource for data analytics in the company? The ideal candidate has a knack for seeing solutions in sprawling data sets and the business mindset to convert insights into strategic opportunities for our company. Role & Responsibilities • Work closely with global & regional teams to architect, develop, and maintain advanced reporting and data visualization capabilities on large volumes of data to support analytics and reporting needs across products, markets and services. • Obtain data from multiple sources, collate, analyze, and triangulate information to develop reliable fact bases. Effectively use tools to manipulate large-scale databases, synthesizing data insights. • Execute cross-functional projects using advanced modeling and analysis techniques to discover ins
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