Consultant, Data Scientist-2
Who is Mastercard?
We are the global technology company behind the world's fastest payments processing network. We are a vehicle for commerce, a connection to financial systems for the previously excluded, a technology innovation lab, and the home of Priceless ®. We ensure every employee has the opportunity to be a part of something bigger and to change lives. We believe as our company grows, so should you. We believe in connecting everyone to endless, priceless possibilities. Job Title
Consultant, Data Scientist-2
Consultant, Data Science, Enterprise Architecture
Career Level 6
The mission of the enterprise architecture data science practice is data actualization: the realization of the full potential of information our data contains to help drive revenue and improve operational efficiencies/cost savings.
As a data scientist at Mastercard your focus will be to design and improve a new breed of AI-driven products. We need you to bring analytical rigor and expertise in data science methods to the challenges we face everyday using petabytes of data to improve Mastercard's products and services.
First and foremost we are part of an engineering organization. As part of enterprise architecture data scientists routinely work on massively scalable deployments that impact millions of merchants and consumers. In our organization we improve company performance by extracting information from our data with the use of sophisticated mathematical and statistical techniques including AI, machine learning, time-series forecasting, and collaborative filtering. We also enable allied teams across the company do the same by evaluating emerging AI technologies for possible inclusion in our data science environment.
We are looking for an experienced data scientist/machine learning engineer who is curious, loves to learn, and eager to work in a collaborative environment. The person in this role will work closely with our data scientists and enterprise architects to both help solve business problems with the use of AI and enable other data science teams to do the same.
•You will work with massive and complex data sets to solve non-trivial business problems while applying advanced analytical methods. Some of these data sets may be transaction-oriented while others are unstructured.
•You will participate in various projects across the organization following our engagement model, the Cross Industry Standard Process for Data Mining.
•You will iteratively build proof of concept pipelines while gaining a clear understanding of business operations and data needed to solve problem statements for specific projects.
•You will evaluate and test emerging AI technologies and use your understanding of Mastercard architectual needs and standards to make recommendations on adoption.
•You will present your findings to various business partners while building and maintaining strong relationships with internal Mastercard partners.
•You will be a part of a cross-functional team working on on R & D projects.
All About You:
•You have demonstrated ability to think creatively with data and apply appropriate data science tools to solve a given complex analysis problem.
•You possess strong problem solving skills including experience with machine learning on large data sets.
•You are self-motivated and capable of working independently but within a collaborative culture.
•You have experience with Hadoop, R, Python, and SQL in large Unix environments. Any project experience with fast data using Kafka and Spark is a plus.
•You have sound understanding of statistical and predictive modeling including time series analysis.
•You have solid understanding of software engineering and enterprise architectural principles. We are particularly interested in individuals with work experience in containerization using Docker and Kubernetes.
•You have a natural ability to pick up new tools and technologies. The only constant in our organization is technological change.
•You have excellent oral and written communication skills.
•You have Master's degree in mathematics, computer science or related field or a bachelor's degree with significant experience required.
Mastercard is an inclusive Equal Employment Opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law.
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