Lead AI/ML Data Engineer

Mastercard; London; On-site; GBP 75,000 - 95,000; Full time

Job summary

A leading financial services company in London seeks a Lead AI/ML Data Engineer to design and deploy cutting-edge machine learning features. The ideal candidate will have over 8 years of experience, proficiency in Python, Scala, or Java, and expertise in building data pipelines. This role offers a full-time position with opportunities for innovation and collaboration across teams.

Qualifications

• Minimum of 8+ years of experience in AI/ML feature engineering or data engineering.
• Strong focus on building and deploying AI/ML feature pipelines in production.
• Experience with big data technologies and MLOps tools.

Responsibilities

• Design, develop, and implement advanced features for machine learning models.
• Build and optimize efficient data pipelines for AI/ML applications.
• Provide technical guidance and mentorship to junior engineers.
• Work with cross-functional teams to translate business problems into technical solutions.

Skills

Python

Scala

Java

Pandas

NumPy

Spark

Cloud platforms

SQL

NoSQL

Docker

Kubernetes

CI/CD for ML

Analytical skills

Communication

Education

Bachelor's degree in Computer Science, Engineering, Data Science

Tools

Cloud platforms

Docker

Kubernetes

Job description

Overview

Lead 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 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