Lead Machine Learning Engineer - Tiger Graph

Our Purpose We 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 culture of inclusion 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 Summary Lead Machine Learning Engineer - Tiger Graph Data Scientist, Engineering Focused – Data and Analytics 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 Foundational AI team is looking for a data scientist with a particular interest in operationalizing and scaling graph-based ML/AI applications who is eager to take on the responsibility of contributing to a wide variety of data science projects. The person in this role will be join a team of leading edge data scientists who are not just building models, but are working to solve foundational business problems for the Company. Experience working with graph databases is highly desired Role In this role you will responsible for: • Leading the deployment of machine learning models and associated data flows to production • Contributing to the automation of the model deployment process • Mentoring junior team members • Searching cleaning, aggregating large data sets from Cloudera Hadoop, Azure, Splunk • Application development and maintenance on Linux environments • Performing statistical data analysis • Iteratively training and retraining Machine Learning systems and models • Extending existing ML frameworks and libraries • Data visualization and story telling with Tableau, Jupyter, RShiny and/or d3s • Graph analytics with Python, R or TigerGraph About You • Experience working with Tiger Graph or other graph DB technologies • Programming with Python and/or R languages • Programming within ML Frameworks such as TensorFlow, PyTorch, scikit-learn, and/or Spark/ML • Model deployment with containers such as Kubernetes and/or Docker • Anomaly detection and model/data drift analysis affecting production ML models • Building and maintaining ML production pipelines • Solid verbal and written communication skills • Bachelor of Science in Computer Science, Engineering, or Mathematics or similar field • Proficient experience working as a machine learning engineer • Experience with a Fortune 500 Company a plus #AI Mastercard is an inclusive equal opportunity employer that considers applicants without regard to gender, gender identity, sexual orientation, race, ethnicity, disabled or veteran status, or any other characteristic protected by law. In the US or Canada, if you require accommodations or assistance to complete the online application process or during the recruitment process, please contact reasonable_accommodation@mastercard.com and identify the type of accommodation or assistance you are requesting. Do not include any medical or health information in this email. The Reasonable Accommodations team will respond to your email promptly. 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. In line with Mastercard’s total compensation philosophy and assuming that the job will be performed in the US, the successful candidate will be offered a competitive base salary based on location, experience and other qualifications for the role and may be eligible for an annual bonus or commissions depending on the role. Mastercard benefits for full time (and certain part time) employees generally include: insurance (including medical, prescription drug, dental, vision, disability, life insurance), flexible spending account and health savings account, paid leaves (including 16 weeks new parent leave, up to 20 paid days bereavement leave), 10 annual paid sick days, 10 or more annual paid vacation days based on level, 5 personal days, 10 annual paid U.S. observed holidays, 401k with a best-in-class company match, deferred compensation for eligible roles, fitness reimbursement or on-site fitness facilities, eligibility for tuition reimbursement, gender-inclusive benefits and many more