Recruitment Team at American Express
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American Express - Business Analyst - Enterprise Digital Analytics (0-3 yrs)
Why American Express?
There's a difference between having a job and making a difference.
American Express has been making a difference in people's lives for over 160 years, backing them in moments big and small, granting access, tools, and resources to take on their biggest challenges and reap the greatest rewards. We- ve also made a difference in the lives of our people, providing a culture of learning and collaboration, and helping them with what they need to succeed and thrive. We have their backs as they grow their skills, conquer new challenges, or even take time to spend with their family or community. And when they- re ready to take on a new career path, we- re right there with them, giving them the guidance and momentum into the best future they envision.
Because we believe that the best way to back our customers is to back our people.
The powerful backing of American Express.
Don't make a difference without it.
Don't live life without it.
American Express is heavily invested to grow its consumer lending portfolio across the card and non-card lending products and services in each of American Express- markets. Global Lending & Cobrand (GLC) is at the heart of this focused on unlocking lending share of existing American Express Card Members and attracting new lending prospects, delivering products and services that will enhance the company's competitive position in each of its markets, and strengthening American Express- brand in the lending space. GLC is a business focused team with colleagues having diverse work-profile from product & marketing to analytics & technology.
The Lending Economics team operating out of Gurgaon, India is responsible for ensuring our business decisions are created on strong economic foundations which have the resilience to withstand multiple business cycles. The team is involved in driving analytics for key lending features & products in US & International markets like Pay It Plan It, Personal Loans, Co-brand products (eg. Hilton, Air miles), etc. The team is also responsible for driving alignment in key structural frameworks for company-wide investment decision making like Card Member Value, Net Credit Margin to ensure a consistent decision making in each area of the business.
- Execute strategic analysis across American Express Proprietary & Co-brand markets to identify revenue generating opportunities and inform pricing strategies
- Execute quantitative analyses to diagnose, inform and validate customer behavioral assumptions on Lending products in multiple focus segments
- Partner with other business units in the company on key Lending decisions across the customer lifecycle, and facilitate information sharing
- Maintain economic inputs underlying profit-based underwriting decisions (acquisitions, credit limit management, cross-sell, customer management) and ensure inputs are refreshed and updated proactively
- Work with multiple business & technical teams to deploy strategies that grow Amex's rightful share of lend, a perception of lend, profitably expand eligibility of products & customer treatments and increase customer engagement while improving the customer experience
- Develop and maintain tracking of key performance metrics for lending business across markets.
- Fully understand market regulations and ensure strategies are 100% compliant with policies and legislation
Critical Factors to Success (Outcome Driven):
- Drive billing, revenue, profitability & lending share growth through advanced analytical techniques
- Drive agile decision making to launch best-in-class products & experience for our card members
- Ensure sound economics in our products to withstand multiple business cycles
- 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 the 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 Critical Factors to Success:
- Build cutting edge and customized Machine Learning/Artificial Intelligence algorithms to enhance modeling accuracy and efficiency
- Innovate modeling techniques and variable creation to solve business problems
- Support analytics across the lifecycle from pre-sales to attrition
- Knowledge and experience of statistical and analytical techniques is preferred. Competency in standard data mining and advanced deep learning techniques is also desirable e.g. Decision trees and Neural Networks
- Exposure to analysis/modeling of digital data is a plus.
- Practical coding experience with statistical analysis programming languages such as SAS, SQL, HIVE, Python and Pysprak. Knowledge/Exposure to Big data is again a plus.
- Bachelor's in Statistics/Mathematics/Economics/ Engineering with relevant experience of 0-3 years
- Post Graduate in Statistics/Mathematics/Economics/ Engineering/Management
- Understanding of financial, credit bureau and behavioral data to develop business insights shaping growth strategies and initiatives
- Strong understanding of the economics of lending products, pricing principles and key levers of profitability
- Understanding of regulations and policies
- Analytics & Insights & Targeting
- R, Python, SAS, SQL
- Hive, Pyspark
- Advanced Statistical Techniques: Gini, Concordance, F-Score
Knowledge of Platforms:
- Big Data - Cornerstone
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
Job type- Permanent
Industry Type - Operations
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