Senior Director, Data Scientist - US Card

Description

The company started as a startup in 1988, when it changed credit card offers by personalizing each one with statistical modeling and relational databases. It has since grown into a Fortune 200 company and a leader in data-driven decision-making.

The role sits in the US Card Data Science group, which builds and deploys statistical and machine learning models across the credit card lifecycle: marketing, acquisitions, underwriting and fraud prevention. The team uses the latest computing and machine learning tools on billions of customer records to help ordinary customers save money, time and hassle.

The models the team builds shape financial products that serve and protect millions of cardholders every day.

Responsibilities

• Work with data scientists, software engineers and product managers to ship products customers like.
• Find insights in large volumes of numeric and textual data using tools such as Python, Conda, AWS, H2O and Spark, among others.
• Build machine learning models at every stage, from design and training through evaluation, validation and implementation.
• Explain your technical work in plain business terms so stakeholders can act on it.

Requirements

• Put customers first and make decisions that are right for them.
• Keep up with published state-of-the-art methods and tools, and look for ways to apply them.
• Take on large, poorly defined problems, ask hard questions and push for answers. Share new ideas freely.
• Challenge the status quo with stakeholders and help develop talent on your team and beyond.
• Be comfortable with open-source languages and keep building your skills in them. Have hands-on experience with data science solutions using open-source tools and cloud platforms.
• Have built, validated and backtested models, and know how to read a confusion matrix or ROC curve. Have experience with clustering, classification, sentiment analysis, time series and deep learning.
• Retrieve, combine and analyze data from varied sources and structures. Understand the data first, since that is often what makes data science work.
• Hold, or be working toward, one of the degrees below, with the degree expected on or before the scheduled start date.
• Bachelor's degree in a quantitative field such as statistics, economics, operations research, analytics, mathematics, computer science or a related field, plus 11 years of data analytics experience.
• Master's degree in a quantitative field as listed above, or an MBA with a quantitative concentration, plus 9 years of data analytics experience.
• PhD in a quantitative field as listed above, plus 6 years of data analytics experience.
• At least 6 years of experience using open-source programming languages for large-scale data analysis.
• At least 6 years of machine learning experience.
• At least 6 years of experience with relational databases.
• Preferred: PhD in a STEM field (science, technology, engineering or mathematics), plus 7 years of data analytics experience.
• Preferred: At least 1 year of experience working with AWS.
• Preferred: At least 4 years of experience managing people.
• Preferred: At least 6 years of experience in Python, Scala or R for large-scale data analysis.
• Preferred: At least 7 years of machine learning experience.

Conditions

The company will consider sponsoring a new qualified applicant for employment authorization for this role.

Full-time annual base salary ranges for Sr Dir, Data Science: Cambridge, MA $314,800 to $359,300; McLean, VA $314,800 to $359,300; New York, NY $343,400 to $392,000.

These ranges apply only to work performed in those locations and show what the company is willing to pay at the time of posting.

Part-time salaries are prorated based on the regular hours agreed.

Candidates hired in other locations are subject to the pay range for that location, and the exact salary is stated only in the offer letter.

Applications will be accepted for at least 5 business days.

No agencies, please.

The company is an equal opportunity employer and considers qualified applicants with criminal histories as applicable law requires.

Roles posted in Canada, the United Kingdom or the Philippines are employed by the company's separate local entity in that country.

Benefits

• Comprehensive, competitive and inclusive health, financial and other benefits.
• Performance-based incentive pay, which may include cash bonuses and/or long-term incentives, may be discretionary or non-discretionary depending on the plan.
• Benefit eligibility depends on full- or part-time status, exempt or non-exempt classification and management level.