Lead Data Scientist, Mastercard

Foundry R&D

Salary not provided

SQL

AWS

Python

Postgres

Tensorflow

Hadoop

Azure

Spark

Scikit-Learn

Snowflake

Senior and Expert level

Dublin

Global payments technology company

Be an early applicant

Global payments technology company

1001+ employees

FintechB2CB2BBankingPaymentsCredit cards

Be an early applicant

Salary not provided

SQL

AWS

Python

Postgres

Tensorflow

Hadoop

Azure

Spark

Scikit-Learn

Snowflake

Senior and Expert level

Dublin

1001+ employees

FintechB2CB2BBankingPaymentsCredit cards

Company mission

To connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible.

Job

Company

Role

Who you are

Data engineering and data science experience
Strong skills in Databricks, Snowflake, and other data platforms
Experience with SQL and one or more of the following database technologies: PostgreSQL, Hadoop, or Spark
Experience working with cloud platforms such as Azure or AWS
Experience with Python and one or more of the following machine learning libraries: Spark ML, TensorFlow, scikit-learn, or XGBoost
Good communication skills
Highly skilled problem solver
Exhibits a high degree of initiative
Bachelor’s or Master’s degree in Computer Science, Data Science, Machine Learning/AI, or a related STEM field

What the job involves

The Data Scientist in the Foundry R&D team is responsible for creating data & analytics solutions including deep learning Artificial Intelligence (A.I.) and Machine Learning (M.L.) models that sit atop large datasets
The Data Scientist is responsible for developing full life cycle modeling processes of data analysis, feature engineering, model training, testing, serving and monitoring
Work closely with business owners to understand business requirements and performance metrics relating to data quality and model performance for customer-facing products
Work with multiple disparate data sources and storage systems, and build processes and pipelines to provide cohesive datasets for analysis and modeling
Generate, maintain, and optimize data pipelines for model building and model performance evaluation
Develop, test, and evaluate modern machine learning and AI models
Oversee implementation of models
Evaluate production models based on business metrics to drive continuous improvement
Leverage AI tooling to develop analytics code and data pipelines and to innovate on processes

Our take

Mastercard is in the global payments business, and operates the world's fastest payments processing network. Its products and solutions have become central to everyday commerce across the world, in activities ranging from shopping and travelling to running businesses.

As the economy has become more and more digitized, Mastercard has been a leading player in helping businesses and individuals across the globe embrace card payments and digital banking. One of the world's largest companies, its revenue has seen consistent gain in the last 20 years.

The challenge for modern payments companies is that payments are always changing, as seen in the astronomical rise of contactless payments over the last decade. Mastercard's acquisition of blockchain systems, and an overall focus on leveraging its technology towards a digital economy, has placed the company in good stead to keep up to date with current trends, like cryptocurrency, in the digitized payments world.

Steph

Company Specialist at Welcome to the Jungle

Insights

21% employee growth in 12 months

Glassdoor (4.1)

Company

Company HQ

Purchase, Harrison, NY

Leadership

Michael Miebach

(CEO)

Michael has served in a variety of roles at the company, including President and CPO. They are currently a Board Member at IBM, Accion, the World Resources Institute, the US-India Strategic Partnership Forum, and the Metropolitan Opera. They are also a Trustee of USCIB.

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