At a Glance
- Tasks: Design and develop cutting-edge AI/ML features that drive business value.
- Company: Join Mastercard, a leader in financial technology innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Be at the forefront of AI/ML technology and make a real impact.
- Qualifications: 8+ years in AI/ML feature engineering with strong technical skills.
The predicted salary is between 80000 - 100000 £ per year.
Overview
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 level: Mid-Senior level
Employment type: Full-time
Job function: Information Technology
Industries: Financial Services, IT Services and IT Consulting, and Technology, Information and Internet
Lead AI/ML Data Engineer in London employer: Mastercard
Mastercard is an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration among talented professionals. As a Lead AI/ML Data Engineer, you will have access to cutting-edge technology and the opportunity for continuous growth through mentorship and cross-functional teamwork, all while contributing to impactful projects in the heart of the financial services industry.
StudySmarter Expert Advice🤫
We think this is how you could land Lead AI/ML Data Engineer in London
✨Network Like a Pro
Get out there and connect with folks in the industry! Attend meetups, webinars, or even just grab a coffee with someone who works at Mastercard. Building relationships can open doors that a CV just can't.
✨Show Off Your Skills
Don’t just talk about your experience; demonstrate it! Create a portfolio showcasing your projects, especially those involving AI/ML feature engineering. Share it on platforms like GitHub to let your work speak for itself.
✨Ace the Interview
Prepare for technical interviews by brushing up on your coding skills and understanding of data pipelines. Practice common interview questions related to AI/ML and be ready to discuss how you’ve tackled real-world problems in your past roles.
✨Apply Through Our Website
When you find a role that excites you, apply directly through our website! It shows you're genuinely interested and makes it easier for us to spot your application. Plus, we love seeing candidates who take that extra step!
We think you need these skills to ace Lead AI/ML Data Engineer in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Lead AI/ML Data Engineer role. Highlight your experience with AI/ML feature engineering and data pipelines, and don’t forget to mention any relevant projects that showcase your skills in Python, Scala, or Java.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you’re passionate about AI/ML and how your background aligns with Mastercard’s goals. Be sure to mention specific technologies and methodologies you’ve worked with that are relevant to the role.
Showcase Your Problem-Solving Skills:In both your CV and cover letter, highlight instances where you've successfully translated business challenges into technical solutions. This will demonstrate your analytical skills and ability to work cross-functionally, which is key for this role.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s straightforward, and you’ll be able to submit all your materials in one go. Plus, we love seeing applications come directly from our site!
How to prepare for a job interview at Mastercard
✨Know Your Tech Inside Out
Make sure you brush up on your technical skills, especially in Python, Scala, and the data manipulation libraries like Pandas and NumPy. Be ready to discuss your experience with building and deploying AI/ML feature pipelines, as well as any big data technologies you've worked with.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've translated business challenges into technical solutions. Think about times when you built efficient data pipelines or implemented robust testing processes, and be ready to explain your thought process.
✨Communicate Clearly
Since you'll be working with cross-functional teams, practice articulating complex technical concepts in a way that non-technical stakeholders can understand. This will demonstrate your ability to collaborate effectively and ensure everyone is on the same page.
✨Demonstrate Your Passion for Innovation
Be prepared to discuss any new technologies or methodologies you've adopted in AI/ML. Showing your enthusiasm for innovation and continuous learning can set you apart from other candidates and align you with Mastercard's forward-thinking culture.
