American Express is hiring for a FRESHER entry level Analyst Data Science role in India

Position

• Analyst Data Science
• Entry level analytics and data science role focused on credit risk and fraud risk
• Individual contributor role with strong exposure to business decision making
• Opportunity to work on real time, high impact financial decisions
• Role designed for early career professionals and fresh graduates
• Focus on predictive modeling, analytics driven decision systems, and business insights
• Position embedded within a global analytics and data science center of excellence

Company

• American Express
• Global financial services and payments company
• Known for credit cards, payments, risk management, and financial innovation
• Strong presence across consumer, small business, and enterprise segments
• Organization with long standing focus on analytics driven decision making
• Employer known for strong culture, ethics, and employee support systems
• Operates at global scale impacting millions of customers daily

Location

• Gurugram, Haryana, India
• Bengaluru Urban, Karnataka, India
• Major analytics and technology hubs in India
• Exposure to global stakeholders and international business teams
• Office locations with access to leadership, training, and collaboration

Job type

• Full time employment
• Permanent role within analytics and risk organization
• Direct employment with American Express
• Eligible for company wide benefits and incentives

Job mode

• Hybrid working model
• Combination of office based and remote work
• Flexibility based on business requirements and team needs
• Designed to support productivity and work life balance

Job requisition id

• 26001162

Years of experience

• Zero to thirty months of relevant experience
• Suitable for freshers and early career professionals
• Open to candidates with academic or internship based exposure
• Ideal for candidates starting careers in analytics and data science

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Company description

• American Express is a global financial services organization with a long legacy of trust, innovation, and customer focus
• The company operates across payments, credit, travel, and financial services, serving individuals and businesses worldwide
• American Express is known for its closed loop network, enabling deep insights across customer behavior, spending, and risk
• The organization places strong emphasis on analytics, data driven decision making, and responsible growth
• Employees at American Express are part of a diverse and inclusive community where collaboration and integrity are core values
• The company actively invests in technology, analytics, and machine learning to improve customer experience and manage risk
• American Express supports career growth through learning programs, leadership development, and internal mobility
• The organization promotes a culture where employees are encouraged to think independently, challenge assumptions, and innovate responsibly
• Employee well being is supported through flexible work arrangements, health programs, and financial support initiatives
• American Express aims to create long term value for customers, shareholders, and communities through ethical business practices

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Profile overview

• This role sits within the Credit and Fraud Risk Analytics and Data Science Center of Excellence
• The team plays a central role in ensuring profitable business growth while controlling fraud and credit losses
• Analysts in this role contribute to decisions that impact customer onboarding, spending experience, and fraud prevention
• The position involves working with large scale structured and unstructured data from across the American Express network
• Analysts are expected to translate business problems into analytical frameworks and data science solutions
• The role provides exposure to end to end model development including design, testing, deployment, and monitoring
• Analysts collaborate with business partners, product teams, and global stakeholders
• The work involves balancing risk mitigation with customer experience, ensuring minimal friction for genuine customers
• This role is suitable for individuals who enjoy solving complex problems using data and analytics
• Analysts gain exposure to advanced machine learning techniques and real world financial use cases

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Role responsibilities

• Understand the core business model of American Express and how decisions impact customers and revenue
• Study credit risk, fraud risk, and marketing levers used across financial products
• Analyze large and complex datasets to uncover actionable business insights
• Develop predictive models to support decision making across risk and fraud domains
• Validate models to ensure performance, stability, and business relevance
• Apply economic logic and analytical reasoning to model driven decisions
• Use network level data to create intelligent and relevant customer level insights
• Explore new analytical approaches using big data and machine learning techniques
• Structure findings clearly for communication with senior leaders and partners
• Partner with cross functional teams across geographies
• Stay updated with industry developments in finance, payments, and analytics
• Contribute to continuous improvement of analytics frameworks and methodologies

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Qualifications

• Master degree in economics, statistics, computer science, or related quantitative fields
• MBA with strong analytical focus is acceptable
• Exposure to analytics or data science through academics, internships, or work experience
• Experience range from zero to thirty months in analytics or data related roles
• Strong foundation in statistics, probability, and data analysis concepts
• Ability to manage deliverables and contribute to business outcomes
• Comfortable working in team based environments with diverse stakeholders
• Strong written and verbal communication skills
• Ability to work independently on open ended and unstructured problems
• Willingness to learn new tools, techniques, and business concepts quickly

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Technical skills

• Programming exposure in Python, R, or SAS
• Experience with SQL and data querying
• Familiarity with big data tools such as Hive and Spark
• Understanding of supervised and unsupervised learning techniques
• Knowledge of regression, classification, and clustering methods
• Exposure to neural networks and tree based models
• Awareness of reinforcement learning and Bayesian approaches
• Understanding of feature engineering and data preparation techniques
• Familiarity with distributed computing and large scale data processing

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Preferred qualifications

• Strong coding and algorithmic problem solving skills
• Exposure to high performance computing concepts
• Interest in scalable analytics and production level modeling
• Academic or project experience in advanced machine learning

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Additional info

• Role offers opportunity to work in one of the strongest analytics teams in the financial services industry
• Exposure to real world problems affecting millions of customers
• Access to leadership and mentorship from experienced data scientists
• Opportunity to build long term career in risk analytics and data science
• Competitive compensation structure including incentives
• Health, wellness, and insurance benefits based on location
• Support for financial planning and retirement
• Flexible working arrangements supporting personal and professional needs
• Parental leave and family support benefits
• Learning and career development programs
• Equal opportunity employer with inclusive hiring practices
• Employment subject to background verification as per regulations

Please click here to apply.