Lead Data Scientist at Mastercard

Glencullen, Leinster, Ireland -

Full Time

Start Date

Immediate

Expiry Date

01 Mar, 26

Salary

0.0

Posted On

01 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Statistical Methods, Machine Learning, Predictive Modelling, Data Visualization, Hadoop, Spark, Cloud Platforms, Data Security, Agile Methodologies, Generative AI, Software Engineering, Data Processing, Data Cleaning, Technical Coaching, Project Management

Industry

IT Services and IT Consulting

Description

Job Title: Lead Data Scientist Overview: Who is Mastercard? Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart, and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments, and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all. Overview Are you an experienced data scientist with a passion for technological innovation, have a can-do attitude and strong sense of ownership? The Small and Medium Enterprise (SME) platform is the perfect opportunity for you to assist in the design & development of a world-class unified platform, enabling Small and Medium Enterprises globally. The SME team is looking for a Lead data scientist to own the development of machine learning models and business intelligence projects. You will also work closely with cross-functional teams, including data engineers, data analysts, and software engineers, to drive data-driven decision making throughout the organization. Key Responsibilities • Leads complex data modeling initiatives and projects to derive insights from extracted data to solve critical business questions • Translates client/ stakeholder needs into technical analyses and/or solutions in collaboration with internal and external partners and presents findings and outcomes to clients/ stakeholders • Identify rich data sources and monitors the melding and cleaning of datasets to ensure consistency • Accountable for delivering high quality project solutions and tools within agreed upon timelines and budget parameters and conducting post- implementation reviews • Guides other to develop sophisticated multivariate models and analytic solutions (e.g., dashboards, prototypes) utilizing complex statistical and data science techniques and methods • Delegates and reviews work for junior level colleagues to ensure downstream applications and tools are not compromised or delayed • Serves as a technical coach for junior-level colleagues and develops technical talent via ongoing technical training, peer review etc. All about you • Extensive Expertise in Python or other relevant programming languages. • Strong background in statistical methods, machine learning algorithms, and predictive modelling. • Skilled in using visualization tools like Tableau, Power BI, or similar to represent complex data. • Proficiency in using big data technologies like Hadoop, Spark, or similar frameworks. • Excellent in communicating complex data insights in a clear and effective manner. • Proven ability to manage and deliver data-centric projects successfully. • Eagerness to stay abreast with the latest advancements in data science and technology. • Familiarity with cloud platforms like AWS, Azure, or Google Cloud for data processing and storage. • Knowledge of data security, privacy standards, and compliance regulations. • Working experience in Agile teams, demonstrating skills in adapting to changing requirements, fostering team collaboration, and driving efficient, iterative development processes. • Ability to work effectively in a team and with stakeholders from various backgrounds. What makes you stand out • Proven expertise in deploying machine learning models to cloud-based production environments, showcasing advanced skills in cloud technologies and the ability to scale models efficiently. • Experience with the innovative application of Generative AI in commercial settings, demonstrating the ability to leverage cutting-edge technology for practical business solutions. • Background in the financial industry, providing a deep understanding of the sector's unique data challenges and how to address them effectively. • Solid foundation in software engineering, with a focus on maintaining high code quality, effective version control, and rigorous testing practices, ensuring the development of robust and reliable software solutions. Corporate Security Responsibility Every person working for, or on behalf of, Mastercard is responsible for information security. All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and therefore, it is expected that the successful candidate for this position 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. To find US Salary Ranges, visit People Place. Under the Compensation tab, select "Salary Structures." Within the text of "Salary Structures," click on the link "salary structures 2025," through which you will be able to access the salary ranges for each Mastercard job family. For more information regarding US benefits, visit People Place and review the Benefits tab and the Time Off & Leave tab.

Responsibilities

The Lead Data Scientist will lead complex data modeling initiatives and projects to derive insights from data to solve critical business questions. They will also guide junior colleagues in developing sophisticated models and analytic solutions while ensuring high-quality project delivery.