Senior Manager, Data Science

Your opportunity

At Schwab, you are empowered to make an impact on your career. Here, innovative thought meets creative problem solving, helping us “challenge the status quo” and transform the finance industry together.

The Behavioral AI/ML Analytics (BAMA) team is looking for a dynamic, self-motivated data scientist at the Senior Manager level. The BAMA team leverages predictive modeling and data science expertise to deliver new tools and capabilities that enhance Schwab’s ability to fight financial crime. BAMA supports fraud prevention and anti-money laundering programs within Financial Risk Management (FRM) by building and maintaining predictive models and developing other advanced analytics solutions that solve problems and provide meaningful business value. There’s no shortage of problems to solve, which allows BAMA numerous opportunities to make an impact.

As a Senior Manager, Data Scientist you will play a key role in helping to identify and understand FRM business needs, establishing yourself as a strategic, long-term partner and not just a modeling service. You’ll work collaboratively with internal and external partners to develop modeling solutions supporting high value initiatives. The data scientist in the short term will be developing models within the fraud space but the focus of their work will change over time to include both transaction channel specific and behavioral modeling. The Sr. Manager, Data Scientist has a solid quantitative background, strong business acumen, an eagerness to learn and teach in a team setting, and a passion for solving meaningful problems. The individual should be tech-savvy and familiar with the best practices related to the development of advanced quantitative models.

This is an individual contributor role.

What you have

Required Qualifications:

• M.S. in a quantitative field.
• 5+ years of experience in analytics, data science or related role.
• Advanced proficiency in SQL and Python.

Preferred Qualifications:

• Demonstrated ability to independently and collaboratively complete end-to-end data science projects solving real-world business problems.
• A proactive approach in identifying where data science solutions can provide value.
• Experience in data science and machine learning in fraud risk, payments or financial services domain.
• Solid communication skills with ability to translate mathematical and statistical concepts into easily understood language.
• Curiosity and enthusiasm to learn new tools and techniques.
• Proficiency in applied AI and Machine Learning.
• Familiarity with GCP.