Senior Analyst-Data Science at American Express Company South Africa

Gurugram, haryana, India -

Full Time

Start Date

Immediate

Expiry Date

10 Jun, 26

Salary

0.0

Posted On

12 Mar, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

SAS, R, Python, Hive, Spark, SQL, Active Learning, Transfer Learning, Neural Models, Decision Trees, Reinforcement Learning, Graphical Models, Gaussian Processes, Bayesian Models, Map Reduce, Attribute Engineering

Industry

Financial Services

Description

At American Express, our culture is built on a 175-year history of innovation, shared At American Express, our culture is built on a 175-year history of innovation, shared values and Leadership Behaviors, and an unwavering commitment to back our customers, communities, and colleagues. From delivering differentiated products to providing world-class customer service, we operate with a strong risk mindset, ensuring we continue to uphold our brand promise of trust, security, and service. As part of Team Amex, you'll experience this powerful backing with comprehensive support for your holistic well-being and many opportunities to learn new skills, develop as a leader, and grow your career. Here, your voice and ideas matter, your work makes an impact, and together, you will help us define the future of American Express. Overview of the Business: Credit and Fraud Risk (CFR) team helps drive profitable business growth by reducing the risk of fraud and maintaining industry lowest credit loss rates. It uses 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 risk management as well as enable commerce and drive innovation. A single decision can have many outcomes. And when that decision affects millions of customers, it needs to be the right one. That’s where our Credit & Fraud Risk (CFR) Analytics & Data Science CoE team comes in. The team leads efforts that leverage data and digital advancements to improve risk management as well as enable commerce and drive innovation, every day. Right from targeting the right customer for our products to underwriting them to managing their experience with Amex when they get onboarded, every decision is advised by groundbreaking analytics & data science. We help the company grow its business profitably while delivering the world's best customer experience, all powered by data. We are the backbone of all financial services operations at American Express and impact every aspect of the company. As a part of the team, you’ll have the opportunity to work in one of the best companies for data scientists in the country. You will solve real world business problems while getting exposure to the industry’s top leaders in analytics, data science and machine learning. If you’re passionate about solving complex problems and crafting solutions that impact millions, you should consider a career in CFR. Description on the role Development, deployment and validation of predictive model(s) and supporting use of models in economic logic to enable profitable decisions across risk, fraud and marketing. Responsibilities: Understand the core business of AXP and the levers behind various decisions Analyze large amounts of data to derive business insights and create innovative solutions Leverage the power of closed loop through Amex network to make decisions more intelligent and relevant Innovate with a focus on developing newer and better approaches using big data & machine learning solution Clear articulation and structuring of business findings across prospect and customer domain to the leadership and key partners Maintain external lens and be aware of developments in the field of Finance/Payments/Analytics etc. Minimum Qualifications • MBA, Master’s Degree In Economics, Statistics, Computer Science Or related fields • 24-48 months of experience in analytics, big data workstreams. · Ability to drive project deliverables to achieve business results • Ability to work effectively in a team environment • Strong communication and interpersonal skills • Innovative problem solver with ability to learn quickly and work independently with complex, unstructured initiatives • Ability to Integrate with Cross-Functional Business Partners Worldwide • SAS, R, Python, Hive, Spark, SQL • Unsupervised and supervised techniques -: active learning, transfer learning, neural models, Decision trees, reinforcement learning, graphical models, Gaussian processes, Bayesian models, Map Reduce techniques, attribute engineering Preferred Qualifications • Expertise in Coding, Algorithm, High Performance Computing We back you with benefits that support your holistic well-being so you can be and deliver your best. This means caring for you and your loved ones' physical, financial, and mental health, as well as providing the flexibility you need to thrive personally and professionally: Competitive base salaries Bonus incentives Support for financial-well-being and retirement Comprehensive medical, dental, vision, life insurance, and disability benefits (depending on location) Flexible working model with hybrid, onsite or virtual arrangements depending on role and business need Generous paid parental leave policies (depending on your location) Free access to global on-site wellness centers staffed with nurses and doctors (depending on location) Free and confidential counseling support through our Healthy Minds program Career development and training opportunities American Express is an equal opportunity employer and makes employment decisions without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, 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.

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Responsibilities

The role involves the development, deployment, and validation of predictive models and supporting their use in economic logic to enable profitable decisions across risk, fraud, and marketing domains. Responsibilities include analyzing large datasets to derive business insights, creating innovative solutions, and clearly articulating findings to leadership and partners.