You Lead the Way. We’ve Got Your Back.
At American Express, we know that with the right backing, people and businesses have the power to progress in incredible ways. Whether we’re supporting our customers’ financial confidence to move ahead, taking commerce to new heights, or encouraging people to explore the world, our colleagues are constantly redefining what’s possible — and we’re proud to back each other every step of the way. When you join #TeamAmex, you become part of a diverse community of over 60,000 colleagues, all with a common goal to deliver an exceptional customer experience every day.
Positions in Risk Management lead the development of credit, operational, enterprise, and fraud policies designed to profitably grow the portfolio, while ensuring excellent customer experience. These policies utilize mathematical models and other techniques to understand and predict customer behavior. At the manager level, the employee does not have a people leadership role but is often viewed as an emerging expert in the field. Focuses on resolution of complex problems. Conducts analyses, recommends changes to policies, and establishes procedures that affect immediate organization.
The CFR team helps drive profitable business growth by reducing the risk of fraud and maintaining our customers' confidence in the security of our products. It utilizes an array of tools and ever-evolving technology to detect and combat fraud, minimize the disruption of good spending and provide a world-class customer experience. The team leads efforts that leverage data and digital advancements to improve service and risk management as well as enable commerce and drive innovation. CFR is responsible for developing and monitoring statistical models for predicting individual and commercial' behaviors such as credit risk, fraud risk, spending and revolve. These models are used for key business decisions made across the customer life cycle to manage risk and accelerate profitable business growth. Underpinning our growth as a company are the tools and capabilities that ensure we prudently take and manage risk in a viable way.
Purpose of the Role:
Develop and enhance existing American Express statistical/deep-learning models by leveraging best-in-class modeling techniques and new data across various stages of card member lifecycle.
- Research on enhancing existing Machine Learning and NLP algorithms for decision science applications and explore new techniques for solving specific business problems
- Explore new Consumer/Commercial unstructured data sources to enhance credit decision science across portfolios
- Create new Data Products/new insights from Data science and establish regular communication with decision science leaders
- Use techniques from artificial intelligence/machine learning/deep learning to solve supervised and unsupervised learning problems.
- Partner with modeling teams to create new/enhance existing variables through regular case reviews
- Provide People and thought leadership for 2 band 30 employees based out of Bangalore
Critical Factors to Success
- Drive billing, revenue growth and profitability through advanced analytical techniques
- Ensure Modeling Accuracy and enhance modeling efficiency in existing processes using Machine Learning
- Innovate Modeling Techniques and Variable creation
- Should possess strong analytical, problem solving skills with research oriented approach and a tremendous will to win.
- Sound knowledge of Machine learning algorithms/econometrics/statistics/data mining and research methods. Candidates with relevant certified patents will have an added advantage.
- Put enterprise thinking first, connect the role’s agenda to enterprise priorities and balance the needs of customers, partners, colleagues & shareholders.
- Lead with an external perspective, challenge status quo and bring continuous innovation to our existing offerings
- Demonstrate learning agility, make decisions quickly and with the highest level of integrity
- Lead with a digital mindset and deliver the world’s best customer experiences every day
At least 3-4 years of industry experience in Machine Learning with focus on Natural Language Processing (NLP), Supervised and Unsupervised techniques on Unstructured Text.
Experience in R/Python/Pyspark programming and Statistical/Deep Learning modeling.
PhD or Post-Graduate degree in Computer Science/Mathematics is preferred
- Data Science/Machine Learning/Artificial Intelligence/NLP on Unstructured Data
- Expertise in Coding, Algorithm, High Performance Computing
- Unsupervised and supervised techniques -: word embedding techniques, clustering, active learning, transfer learning, neural models, Decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, Map Reduce techniques, attribute engineering
- Deep learning, Gradient boosting machines, self-reinforcing algorithms
- Sound knowledge of NLP/Machine Learning algorithms and latest developments in Open Source technologies for unstructured data. Experience with capturing, managing and processing Big Data will be an added advantage.
Knowledge of Platforms
- Hands on experience in open source tools and techniques such as hive/python/pyspark. Familiarity with Keras/Tensor Flow frameworks for deep learning models.
Enterprise Leadership Behaviors
• Set The Agenda: Define What Winning Looks Like, Put Enterprise Thinking First, Lead with an External Perspective
• Bring Others With You: Build the Best Team, Seek & Provide Coaching Feedback, Make Collaboration Essential
• Do It The Right Way: Communicate Frequently, Candidly & Clearly, Make Decisions Quickly & Effectively, Live the Blue Box Values, Great Leadership Demands Courage
American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability status, age, or any other status protected by law.
Offer of employment with American Express is conditioned upon the successful completion of a background verification check, subject to applicable laws and regulations.
Schedule (Full-Time/Part-Time): Full-time
Date Posted: Feb 26, 2021, 2:39:23 AM