Senior Data Scientist

Posted Yesterday
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Hiring Remotely in Dublin, IRL
Remote or Hybrid
Senior level
Blockchain • Fintech • Payments • Consulting • Cryptocurrency • Cybersecurity • Quantum Computing
We are a global technology company in the payments industry.
The Role
Design, build, validate, and deploy advanced ML models and analytic solutions on large/complex datasets. Collaborate with stakeholders, perform QA on prototypes, present actionable insights, and support data R&D while following coding and documentation best practices.
Summary Generated by Built In
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
Senior Data Scientist
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
The Small Business team is looking for a Data Scientist who is passionate about data analysis, Machine Learning, and Artificial Intelligence. The person in this role will be joining a cross-functional team who are not just building models but are working to solve foundational business problems for our customers. The ideal candidate is comfortable working with Big data sources and able to implement and validate predictive models to provide insights and solutions for different business problems. The person in this role will be responsible for data interpretation and presentation to aid business partners in making informed data-driven decisions to improve business outcomes. The right candidate is able to collaborate with other data scientists and various internal business partners to help solve business problems using advanced ML/AI. The person in this role must be organized and follow best practices in coding and documentation.
RESPONSIBILITIES:
- Independently manages and manipulates large data sets and applies various technical and statistical analytical techniques (e.g., OLS, multinomial logistic regression, LDA, clustering and segmentation) to draw insights from large data sets
- Communicates with client counterparts to ensure customer needs are being addressed when designing data analyses and technical solutions
- Reviews and applies complex analytical techniques or tools to draw meaningful and insightful observations and trends from large/ complex data sets
- Develops sophisticated multivariate models and analytic solutions (e.g., dashboards, prototypes), utilizing complex statistical and data science techniques and methods
- Meets project deadlines for accountable deliverables and anticipates delays or foreseeable barriers to progress, escalating issues when necessary
- Conducts due diligence quality assurance testing for prototypes and tools in beta and resolves reoccurring complex issues and bugs
- Assist with data R&D work as delegated by senior level colleagues
ALL ABOUT YOU
- Demonstrated ability to combine, interrogate, and manipulate large data sets.
- Extensive experience of using common programing languages (Python preferred) and different statistics and machine learning libraries (Pandas, scikit-learn, PySpark etc)
- Experience with big data tools (e.g., Hadoop, impala or spark)
- Extensive experience leveraging open-source tools, predictive analytics, machine learning, and other data techniques to perform complex analyses for project work.
- Understand the trade-off between different model validation metrics to achieve the most optimal mode performance based on the business needs.
- Knowledge of version control systems (Git etc).
- Consistently delivered accurate, technically advanced, and valid analyses with impactful insights and conclusions
- Demonstrated success when deciding on technical methodologies for project work
- Track record handling direct client communications professionally and effectively
- Served as an expert resource or go-to person for a specific consulting tool(s), system(s), and/or application(s)
- Good to have experience with BI visualization tools (Tableau, Domo, Power BI etc)
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.

Skills Required

  • Experience combining, interrogating, and manipulating large data sets
  • Extensive experience with programming languages (Python preferred)
  • Experience with data libraries and ML frameworks (Pandas, scikit-learn, PySpark)
  • Experience with big data tools (Hadoop, Impala, Spark)
  • Experience leveraging open-source tools and predictive analytics/machine learning for complex analyses
  • Understanding trade-offs between model validation metrics and selecting optimal metrics for business needs
  • Knowledge of version control systems (Git)
  • Demonstrated ability to communicate with clients and translate analysis into business decisions
  • Experience conducting quality assurance testing for prototypes and resolving recurring issues
  • Experience with BI visualization tools (Tableau, Domo, Power BI)

What the Team is Saying

Jenny
Mastercard

Mastercard Compensation & Benefits Highlights

  • Retirement Support Company information highlights a 10% retirement match on U.S. roles, positioned as best‑in‑class and well above typical large‑employer benchmarks. This level of employer contribution materially strengthens long‑term savings.
  • Leave & Time Off Breadth U.S. postings list 25 vacation days, 5 personal days, 10 company holidays, 80 hours of paid sick/safe time, and up to 20 days of bereavement. A minimum of 16 weeks paid new‑parent leave (including adoption and foster) further expands paid time away.
  • Parental & Family Support Benefits include a minimum of 16 weeks paid new‑parent leave and family‑building support such as fertility, adoption, and surrogacy where legally available. Dependent scholarships, counseling, and protection benefits contribute additional family support.

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The Company
HQ: Purchase, NY
38,800 Employees
Year Founded: 1966

What We Do

Mastercard powers economies and empowers people in 200+ countries and territories worldwide. Together with our customers, we’re building a resilient 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.

Why Work With Us

We live the Mastercard Way: creating value in the communities we touch, growing together through the opportunities we see, and moving fast to innovate and scale. Our collaborative culture and our passionate people are the key to what we do, driving meaningful change as one team and connecting everyone to priceless possibilities.

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Employees engage in a combination of remote and on-site work.

In our ongoing workplace evolution, we’ve introduced hybrid work, Work-From-Elsewhere Weeks and Meeting-Free Days.

Typical time on-site: 3 days a week
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