Senior Manager, Data Science - Model Risk

Description

The company started as a startup in 1988, when it changed the credit card market by tailoring each card offer to the individual using statistical models and relational databases. It has since grown into a Fortune 200 company and a leader in data-driven decisions.

As a Data Scientist on the team, you will help drive the next wave of change at a much larger scale, applying the newest computing and machine learning methods to billions of customer records to find openings that help everyday people save money, time and stress in their finances.

The Model Risk Office guards the company against model failures and looks for ways to make better decisions with models. The team combines statistics, software engineering and business knowledge to improve outcomes in Risk Management and across the enterprise.

The team plans ahead by building new skills, improving tools and maintaining a network of trusted partners. It studies past errors and builds stronger techniques so those errors are not repeated.

Responsibilities

• Work with data scientists, software engineers and product managers to deliver a product customers value.
• Use a broad technology stack, including Python, Conda, AWS, H2O and Spark, to find insights in large volumes of numeric and text data.
• Build machine learning models at every stage, from design and training through evaluation, validation and rollout.
• Translate the technical detail of your work into clear business goals for others.

Requirements

• Hold, or be working toward with completion expected on or before the scheduled start date, one of the following:
• A Bachelor's degree in a quantitative field such as Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science or a related field, plus 7 years of data analytics experience.
• A Master's degree in a quantitative field as listed above, or an MBA with a quantitative concentration, plus 5 years of data analytics experience.
• A PhD in a quantitative field as listed above, plus 2 years of data analytics experience.
• At least 2 years using open source programming languages for large-scale data analysis.
• At least 2 years of machine learning work.
• At least 2 years working with relational databases.
• You question accepted thinking, work with stakeholders to find and fix weak points in current practice, and care about developing talent on your team and beyond.
• You enjoy analysis and building, and you want to make the right decision for customers.
• You keep up with new technologies and published state-of-the-art methods, and you look for ways to apply them.
• You have built, validated and backtested models, can read a confusion matrix or ROC curve, and have experience with clustering, classification, sentiment analysis, time series and deep learning.
• Preferred: a PhD in a 'STEM' field (Science, Technology, Engineering or Mathematics) plus 4 years of data analytics experience.
• Preferred: at least 1 year of experience working with AWS.
• Preferred: at least 1 year of experience managing people.
• Preferred: at least 5 years of experience in Python, Scala or R for large-scale data analysis.
• Preferred: at least 5 years of machine learning experience.

Conditions

Full-time annual salary ranges for Sr Mgr, Data Science by location: Chicago, IL $209,000 - $238,500; McLean, VA $229,900 - $262,400; New York, NY $250,800 - $286,200; Richmond, VA $209,000 - $238,500.

These ranges apply only to candidates hired to work in these locations, and show what the company is willing to pay at the time of posting.

Candidates hired elsewhere receive the pay range for their location, and the exact salary is stated in the offer letter.

Part-time pay is prorated based on the agreed number of regular hours.

Eligibility for benefits varies by full or part-time status, exempt or non-exempt status and management level.

Applications will be accepted for at least 5 business days.

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

Recruitment agencies are not accepted.

Roles posted in Canada are with the Canadian entity, roles in the United Kingdom are with the European entity, and roles in the Philippines are with the Philippines services entity.

The company is an equal opportunity employer that does not discriminate, promotes a drug-free workplace and considers applicants with criminal histories in line with applicable law.

Benefits

• Performance-based incentive pay, which may include cash bonuses and/or long-term incentives (LTI), and may be discretionary or non-discretionary depending on the plan.
• A broad set of health, financial and other benefits to support your overall well-being.