Senior Data Scientist (Machine Learning)

TL;DR

Senior Data Scientist (Machine Learning): Developing and deploying scalable data science models for large-scale payment and business datasets with an accent on deep learning, generative models, distributed systems, and reproducible analytics pipelines. Focus on leading technical project teams, translating complex analytics into business recommendations, and solving large-scale modeling challenges across cross-functional organizations.

Location: Austin, Texas, United States; hybrid work with at least three days in the office. Candidates must be legally authorized to work in the United States now and in the future without employment sponsorship. Travel is required 5–10% of the time.

Salary: $145,300–$232,700 USD per year, with potential bonus, equity, and sales incentive payments where applicable.

Company

Global payments technology corporation facilitating transactions among consumers, merchants, financial institutions, and government entities across more than 200 countries and territories.

What you will do

• Develop and deploy advanced data science models, including deep learning, machine learning, recommendation systems, and generative models.
• Lead technical data science teams and provide direction to ensure rigorous, high-quality outcomes.
• Manage end-to-end data science projects from planning and requirements gathering through delivery.
• Work with large-scale datasets and modern distributed systems to build scalable solutions.
• Translate analytics results into actionable recommendations and communicate complex concepts to senior business audiences.
• Ensure reproducibility and quality across analytic pipelines and project deliverables.

Requirements

• Legal authorization to work in the United States without current or future employment sponsorship.
• At least 5 years of relevant experience with a bachelor's degree, 2 years with an advanced degree, a PhD with no prior experience, or 8+ years of relevant experience.
• Advanced data science, machine learning, statistical modeling, and scalable model development experience.
• Experience extracting and aggregating large datasets using SQL or similar tools and creating reproducible analytic pipelines.
• Expertise in multiple programming languages or platforms such as Python, R, and Spark.
• Experience leading project teams, collaborating cross-functionally, and communicating technical concepts to business stakeholders.

Nice to have

• Experience with Hadoop, Hive, Apache Spark, TensorFlow, PyTorch, or scikit-learn.
• Data visualization experience using Tableau, Power BI, or R/Python.
• Experience in financial services or the payments industry.
• Experience working in global organizations with stakeholders across geographies.

Culture & Benefits

• Hybrid office-based work with expectations of at least three days in the office.
• Medical, dental, vision, 401(k), FSA/HSA, life insurance, paid time off, and wellness benefits may be available.
• Work hours vary according to department needs.
• Opportunity to work on payment technology with impact across global markets.