American Express Remote.jobs @ Get Dream Job

American Express; Denver (CO); Remote; USD 33,000 - 41,000; Full time

Job summary

American Express in the USA seeks a Manager-Data Science to lead machine learning initiatives within the Model Risk Management Group. You will help evaluate concept quality, data quality, and governance while collaborating with business partners and regulators.

Responsibilities include documenting observations, communicating results, exploring algorithms such as gradient boosting and neural networks, and improving modeling governance to support risk management.

Qualifications

• Bachelor's degree required.
• Advanced degree in quantitative field preferred.
• Experience with ML algorithms and data quality essential.
• Knowledge of NLP techniques like BERT or RASA is a plus.

Responsibilities

• Manage model risk and governance within MRMG.
• Assess concept quality and data quality for models.
• Document observations and prepare for audits.
• Communicate results to leadership and regulators.
• Explore ML algorithms and applications for risk management.

Skills

Machine learning

NLP (BERT, RASA)

Big data processing

Communication skills

Deadline-driven

Education

Bachelor's degree

Tools

SAS

Python

R

Java

Scala

C++

Job description

Job Responsibilities: Manager-Data Science Salary: $20-30/Hour Company: American Express Location: USA Educational Requirements: Bachelor\'s Degree Full Job Description: With the right support, people and businesses can make tremendous progress. When you join the Amex team, you\'ll be part of a global community of diverse colleagues committed to supporting our customers, our community and each other. Here, you will learn and grow as we help you create a unique and meaningful career path for the benefits, programs and changes that support you personally and professionally. At American Express, you will be recognized for your contribution, leadership and influence. Everyone who works together has the opportunity to participate in the success of the company. Together, we will win as a team, and strive to support our company values and our strong commitment to support and deliver the best customer experience in the world every day. And we will do this with integrity and an environment where everyone is seen, heard and felt. The Model Risk Management Group (MRMG) is responsible for managing model risk and controlling the use of machine learning across the company. This role will be a key role for financial, banking and anti-money laundering. The person\'s responsibility is also to ensure that there is a high level of productivity and to meet the legal requirements for managing type risks (SR 11-7). This is a very competitive job and one that allows the individual to achieve his/her intellectual and business potential. This role will report to the Director of MRMG. Various services include: Manages financial, banking and financial transactions, including assessment of concept quality, data quality, operational support and ongoing monitoring. Accurately document sample observations and prepare for systematic and internal audits Communicate model analysis results to business partners, senior management and regulators Explore machine learning algorithms and their applications and models Improve governance to take into account the initiation of modeling processes, model development, and model risk management.

Eligibility

• advanced degree in quantitative field
• Hands-on presentation experience preferred
• A qualified candidate should have a good understanding of machine learning algorithms (e.g. gradient boosting, XGBoost, neural networks), artificial intelligence, deep learning and classical modeling and computation theory. Knowledge of NLP techniques like BERT, RASA is a plus
• Experience in big data processing and management is a plus - familiarity with big data platforms and applications, such as Hadoop, Pig, Hive, Spark, AWS.
• Must be proficient in coding in SAS and/or Python/R; Also, Java, Scala and C++ are optional.
• Strong communication and writing skills
• Flexibility and adaptability to work under deadlines and changing priorities