Lead Machine Learning Engineer- Merchant Data Platform @ Visa

Essential Functions:

• Collaborate with project team members (Product Managers, Architects, Analysts, Software Engineers, Project Managers, etc.) to ensure development and implementation of new data driven business solutions.
• Drive development effort End-to-End for timely delivery of high quality solutions that conform to requirements, conform to the architectural vision, and align with all applicable standards. Responsibilities span all phases of solution development.
• Collaborate with senior technical staff and PM to identify, document, plan contingency, track and manage risks and issues until all are resolved.
• Present technical solutions, capabilities, considerations, and features in business terms. Effectively communicate status, issues, and risks in a detailed and timely manner.

This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.

Basic Qualifications:

• 10 or more years of work experience with a Bachelor’s Degree or at least 8 years of work experience with an Advanced Degree (e.g. Masters/ MBA/JD/MD) or at least 3 years of work experience with a PhD.

Preferred Qualifications:

• 12 or more years of work experience with a Bachelor’s Degree or 8-10 years of experience with an Advanced Degree (e.g. Masters, MBA, JD, MD) or 6+ years of work experience with a PhD.
• Relevant working experiences in modeling techniques such as logistic regression, Naive Bayes, SVM, decision trees, or neural networks.
• Skilled in SQL, Python and basic libraries for machine learning such as scikit-learn and Pandas, as well as Jupyter Notebook.
• Experience with Big Data and analytics in general leveraging technologies like Hadoop, Spark, and Query Engines.
• Experience with Natural Language Processing and Deep Learning.
• Experience in MLOps and production machine learning systems at large scale.
• Experience in Automation framework such as Airflow or Metaflow.
• Experience in mentoring junior talents and technical leadership.