Machine Learning Engineer

Our PurposeWe work 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 We cultivate a for all employees that respects their individual strengths views and experiences We believe that our differences enable us to be a better team - one that makes better decisions drives innovation and delivers better business results Title and SummaryMachine Learning EngineerOverview We are the global technology company behind the worlds fastest payments processing network We are a vehicle for commerce a connection to financial systems for the previously excluded a technology innovation lab and the home of Priceless xc2 xae We ensure every employee has the opportunity to be a part of something bigger and to change lives We believe as our company grows so should you We believe in connecting everyone to endless priceless possibilities Our team within Mastercard - Data Services The Data Services team is a key differentiator for Mastercard providing the cutting-edge services that are used by some of the world s largest organizations to make multi-million dollar decisions and grow their businesses Focused on thinking big and scaling fast around the globe this agile team is responsible for end-to-end solutions for a diverse global customer base Centered on data-driven technologies and innovation these services include payments-focused consulting loyalty and marketing programs business Test Learn experimentation and data-driven information and risk management services Targeting Analytics Program Within the D S Technology Team the Targeting Analytics program is a relatively new program that is comprised of a rich set of products that provide accurate perspectives on Credit Risk Portfolio Optimization and Ad Insights Currently we are enhancing our customer experience with new user interfaces moving to API-based data publishing to allow for seamless integration in other Mastercard products and externally utilizing new data sets and algorithms to further analytic capabilities and generating scalable big data processes We are seeking an innovative ML Engineer to share responsibility in designing and building a full stack web application and data pipelines The goal is to deliver custom analytics efficiently leveraging machine learning and AI solutions This individual will thrive in a fast-paced agile environment and partner closely with other areas of the business to build and enhance solutions that drive value for our customers Engineers work in small flexible teams Every team member contributes to designing building and testing features The range of work you will encounter varies from building intuitive responsive UIs to designing backend data models architecting data flows and beyond There are no rigid organizational structures and each team uses processes that work best for its members and projects Here are a few examples of products in our space Portfolio Optimizer PO is a solution that leverages Mastercards data assets and analytics to allow issuers to identify and increase revenue opportunities within their credit and debit portfolios Audiences uses anonymized and aggregated transaction insights to offer targeting segments that have high likelihood to make purchases within a category to allow for more effective campaign planning and activation Credit Risk products are a new suite of APIs and tooling to provide lenders real-time access to KPIs and insights serving thousands of clients to make smarter risk decisions using Mastercard data Help found a new fast-growing engineering team Role Responsibilities Work as a member of an agile team to design build test and deploy new products and features Build and deploy AI solutions that should work at scale Build appropriate data pipelines to support model deployments Optimize large models for efficiency and scalability Monitor the AI models and applications that are deployed Lead and own everything around Machine Learning Operations Prepare appropriate documentation of the model deployment and processes Conduct root cause analysis of data pipeline and other processes Participate in code reviews model review testing and debugging for high quality product Conduct data analysis for different use-cases Conduct data extraction data analysis data cleaning preparation modeling and evaluation Support building prototypes and proof-of-concepts Collaborate with internal teams and other teams across the company Expert understanding of data pipeline building Snowflake Azure Python Push for better Development Practices better Code better Solutions Proactively understand stakeholder needs goals expectations and viewpoints to deliver results All about you At least 4 years of proven experience in developing and deploying Machine learning and Deep learning solutions Deep understanding of different Machine learning Deep learning and AI algorithms High proficiency in using Python and R Hands on experience on ML Frameworks Scikit learn and Deep Learning Framework TensorFlow PyTorch Solid experience with SQL Hadoop and or Snowflake databases Good understanding of Cloud technology Building and maintaining ML production pipelines Curious Critical thinker good hacking skills and scientific reasoning Strong familiarity with Software engineering practices Not afraid to ask questions and propose new ideas Strong technologist eager to learn new technologies and frameworks Corporate Security ResponsibilityAll 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 Mastercards security policies and practices Ensure the confidentiality and integrity of the information being accessed Report any suspected information security violation or breach andComplete all periodic mandatory security trainings in accordance with Mastercards guidelines