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- Tasks: Design and develop cutting-edge AI/ML features that drive business value.
- Company: Join Mastercard, a global leader in digital payments, empowering economies worldwide.
- Benefits: Enjoy competitive salary, remote work options, and a vibrant company culture.
- Why this job: Be at the forefront of innovation, influencing products and strategies in a dynamic environment.
- Qualifications: Bachelor's degree and 8+ years in AI/ML feature engineering or data engineering required.
- Other info: Work collaboratively with cross-functional teams and mentor junior engineers.
The predicted salary is between 42000 - 84000 £ per year.
OverviewLead AI/ML Data Engineer role at Mastercard . You will be at the forefront of designing, developing, and deploying cutting-edge machine learning features that drive core business value for Mastercard. You will leverage your deep technical expertise to build sophisticated data pipelines and engineer impactful features, directly influencing our products and strategies.
Responsibilities
Design, develop, and implement advanced features from raw data for various machine learning models, ensuring their relevance, robustness, and scalability
Build and optimize efficient and reliable data pipelines to support the ingestion, transformation, and delivery of data for AI/ML applications
Provide technical guidance and mentorship to other junior engineers
Work closely with AI engineers, product managers, and other engineering teams to understand requirements, translate business problems into technical solutions, and integrate AI/ML features into production systems
Support the deployment, monitoring, and maintenance of AI/ML features in production environments
Implement robust testing and validation processes to ensure the quality, accuracy, and reliability of engineered features and AI/ML data pipelines
Qualifications
Education: Bachelor\\\’s degree in Computer Science, Engineering, Data Science, or a related quantitative field
Experience: Minimum of 8+ years of experience in AI/ML feature engineering, data engineering, or a related field, with a strong focus on building and deploying AI/ML feature pipelines in production
Technical Skills: Proficiency in Python, Scala, or Java
Extensive experience with data manipulation and analysis libraries (Pandas, NumPy, Spark)
Hands-on experience with cloud platforms
Strong background in SQL and NoSQL databases
Experience with big data technologies
Familiarity with MLOps tools (Docker, Kubernetes, CI/CD for ML)
Analytical and problem-solving skills; ability to translate business challenges into technical solutions
Excellent communication and presentation skills; ability to articulate technical concepts to technical and non-technical stakeholders
Proven ability to work in cross-functional teams and drive projects to completion
Passion for innovation and track record of adopting new technologies and methodologies in AI/ML
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;
Complete all periodic mandatory security trainings in accordance with Mastercard\’s guidelines.
Seniority levelMid-Senior level
Employment typeFull-time
Job functionInformation Technology
IndustriesFinancial Services, IT Services and IT Consulting, and Technology, Information and Internet
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Lead AI/ML Data Engineer employer: MasterCard
Contact Detail:
MasterCard Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Lead AI/ML Data Engineer
✨Tip Number 1
Familiarise yourself with Mastercard's core values and mission. Understanding their focus on building a sustainable economy and empowering people will help you align your answers during interviews, showcasing how your skills can contribute to their goals.
✨Tip Number 2
Network with current or former employees of Mastercard, especially those in AI/ML roles. They can provide valuable insights into the company culture and expectations, which can help you tailor your approach when discussing your experience and skills.
✨Tip Number 3
Stay updated on the latest trends and technologies in AI/ML and data engineering. Being able to discuss recent advancements or tools during your interview will demonstrate your passion for innovation and your commitment to staying at the forefront of the field.
✨Tip Number 4
Prepare to discuss specific projects where you've built and deployed AI/ML features. Be ready to explain your thought process, the challenges you faced, and how you overcame them, as this will highlight your problem-solving skills and technical expertise.
We think you need these skills to ace Lead AI/ML Data Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in AI/ML feature engineering and data engineering. Focus on specific projects where you've designed and implemented machine learning models or built data pipelines.
Craft a Compelling Cover Letter: In your cover letter, express your passion for innovation in AI/ML and how your skills align with Mastercard's mission. Mention specific technologies you’ve worked with that are relevant to the role, such as Python, SQL, or cloud platforms.
Showcase Technical Skills: Clearly list your technical skills, especially those mentioned in the job description like proficiency in programming languages, data manipulation libraries, and familiarity with MLOps practices. Use examples to demonstrate your expertise.
Highlight Team Collaboration: Since the role involves working closely with cross-functional teams, include examples of past experiences where you successfully collaborated with others. This could be in mentoring junior engineers or integrating AI/ML features into production systems.
How to prepare for a job interview at MasterCard
✨Showcase Your Technical Skills
As a Lead AI/ML Data Engineer, you'll need to demonstrate your proficiency in programming languages like Python, Scala, or Java. Be prepared to discuss specific projects where you've built and deployed AI/ML feature pipelines, highlighting the technologies and methodologies you used.
✨Understand the Business Impact
Mastercard is focused on driving core business value through technology. Make sure you can articulate how your work in AI/ML has positively impacted previous projects or companies. This will show that you understand the importance of aligning technical solutions with business objectives.
✨Prepare for Technical Questions
Expect to face technical questions related to data engineering, machine learning models, and big data technologies. Brush up on your knowledge of SQL, NoSQL databases, and MLOps practices. Being able to solve problems on the spot will impress your interviewers.
✨Demonstrate Leadership and Mentorship
Since this role involves providing guidance to junior engineers, be ready to discuss your experience in mentoring others. Share examples of how you've led teams or projects, and how you approach fostering a collaborative environment among cross-functional teams.
