American Express is hiring for a fresher entry level Data Scientist role in India

Position:

• (Data Scientist) Analyst – Data Science (SQL, Python, Machine Learning)

Company:

• American Express

Location:

• Gurugram, Haryana, India

Job type:

• Full-time

Job mode:

• Hybrid

Job requisition id:

• 25014288

Years of experience:

• 0–3 years

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Company Description

• American Express is a global financial services leader with a legacy of over 175 years, widely recognized for its customer-first approach, innovative solutions, and strong ethical foundation.

• The company operates in multiple markets worldwide, delivering services in credit cards, charge cards, travel-related services, and financial solutions to individual, corporate, and institutional clients.

• The organization’s culture is based on shared values, leadership principles, and a genuine commitment to empowering employees while ensuring positive customer outcomes.

• American Express is deeply committed to innovation, continuously investing in data-driven solutions and digital transformation to remain a leader in the financial services industry.

• The company promotes a workplace that fosters inclusivity, collaboration, and continuous learning, providing employees with resources and opportunities to develop their careers.

• As part of the team, employees gain access to a range of benefits that address physical, mental, and financial well-being, ensuring both personal and professional growth.

• American Express prides itself on making decisions based on fairness, equality, and compliance with global employment standards.

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Profile Overview

• This role is part of the Commercial Data Quality & Data Products Analytics team within the Analytics, Investments, and Marketing Enablement (AIM) division of American Express.

• The AIM team focuses on driving the acquisition, engagement, and retention of commercial customers across various online and offline channels.

• The role emphasizes delivering high-quality data products, insights, and analytics that enhance targeting and marketing strategies for the Global Commercial Services (GCS) business.

• The Analyst will work on projects that enrich the quality of commercial data elements, leveraging advanced methodologies like machine learning for improved decision-making.

• A key responsibility is to collaborate with cross-functional teams, influence business strategies, and contribute to the development of analytical solutions that impact marketing and sales outcomes.

• The environment is fast-paced and collaborative, requiring a blend of technical expertise, problem-solving abilities, and effective communication skills.

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Qualifications

• Educational background: Master’s degree or MBA in a quantitative discipline such as Finance, Engineering, Physics, Mathematics, Computer Science, or Economics.

• Strong programming skills in SAS and SQL, with proven experience working on large structured and unstructured datasets.

• Understanding of recommendation system methodologies like collaborative filtering, k-nearest neighbors, association rules, market basket analysis, and advanced techniques like SVD and matrix factorization.

• Practical experience with big data tools and platforms such as Hadoop, PIG, HIVE, and Mahout.

• Knowledge of data mining and machine learning techniques including regression, clustering, decision trees, neural networks, and SVM.

• Strong communication and interpersonal skills to effectively collaborate with diverse stakeholders.

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Additional Info

• The role comes with competitive salary packages, performance bonuses, and comprehensive health benefits that may include medical, dental, vision, and life insurance depending on location.

• Flexible working arrangements are supported through hybrid, on-site, or virtual setups as per business needs.

• Career development opportunities include mentorship programs, professional certifications, and access to internal training resources.

• The company promotes employee wellness through initiatives like the Healthy Minds program and access to global wellness centers in certain locations.

• Paid parental leave policies and retirement planning support are provided based on location-specific guidelines.

• American Express maintains a strict non-discrimination policy, ensuring that employment decisions are made without bias toward race, gender, religion, or other protected characteristics.

• Employment is subject to successful background verification and compliance with local laws.

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Detailed Paraphrased Job Description 

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Role Purpose and Strategic Importance

• The Analyst – Data Science role exists to enhance the quality and accessibility of commercial data, which is fundamental to American Express’s marketing and sales strategies for business clients.

• By applying advanced analytics and machine learning, the role directly supports the Global Commercial Services division in identifying high-value prospects, improving customer engagement, and driving revenue growth.

• The position bridges the gap between raw data availability and actionable business intelligence, ensuring data integrity, accuracy, and usability across various platforms and campaigns.

• This function is vital in creating data products that improve targeting precision, campaign personalization, and overall customer experience.

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Key Responsibilities – In Depth

• Data Quality Enrichment

  • Assess existing datasets for completeness, accuracy, and timeliness.

  • Implement corrective measures to address data gaps or inconsistencies, ensuring improved reliability for downstream analytics.

  • Develop algorithms and workflows to automate the data cleansing process, thereby increasing operational efficiency.

  • Apply statistical checks and data governance protocols to maintain high data standards across systems.

• Development of Innovative Data Products

  • Design and build data products that serve specific marketing and targeting use cases.

  • Examples include predictive models like Product/Channel Propensity Scores, which estimate the likelihood of a customer responding to a given marketing channel.

  • Develop Best Time to Call algorithms that optimize outbound sales outreach based on historical response patterns.

  • Create indices such as the Lead Quality Index (LQI) to prioritize sales efforts toward the most promising leads.

  • Identify commercial expense categories to inform cross-selling strategies and partnership opportunities.

• External Data Integration

  • Partner with third-party data providers to evaluate the potential value of new datasets.

  • Conduct proof-of-concept studies to measure the impact of integrating external small business signals into American Express’s targeting systems.

  • Negotiate with vendors for access to high-quality data sources while ensuring compliance with privacy and legal standards.

• Collaboration with Decision Science and Capabilities Teams

  • Work alongside internal data scientists, data engineers, and business analysts to refine analytical models and ensure accurate data inputs.

  • Share findings and insights with cross-functional teams to guide marketing strategies and sales initiatives.

  • Participate in capability-building initiatives to improve the company’s overall data infrastructure and analytical tools.

• Business Impact and Influence

  • Present analytical findings to senior stakeholders, highlighting actionable insights and recommendations.

  • Use storytelling techniques to translate complex technical results into clear business implications.

  • Contribute to strategic discussions on customer acquisition, retention, and engagement based on empirical evidence from data analysis.

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Tools, Technologies, and Techniques Used

• Programming Languages and Query Tools

  • SAS for advanced statistical modeling and data manipulation.

  • SQL for querying and managing large-scale relational databases.

• Big Data Platforms

  • Hadoop ecosystem for distributed storage and processing.

  • PIG and HIVE for high-level data analysis on large datasets.

  • Mahout for scalable machine learning implementations.

• Machine Learning and Data Mining

  • Regression analysis for identifying key predictors of customer behavior.

  • Clustering techniques for segmenting customers into distinct groups.

  • Decision trees for interpretable predictive models.

  • Neural networks for capturing complex nonlinear patterns.

  • SVM for classification tasks requiring high accuracy.

• Recommendation Systems

  • Collaborative filtering for personalized product recommendations.

  • Association rule mining for uncovering purchase patterns.

  • Matrix factorization for dimensionality reduction and improved recommendation accuracy.

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Career Growth and Development

• Employees in this role can progress toward senior analyst or data scientist positions within American Express.

• Exposure to global markets and large-scale datasets provides a strong foundation for future leadership roles in analytics and strategy.

• Opportunities to work on high-impact projects that influence the direction of the company’s commercial marketing approach.

• Access to internal training programs and sponsored certifications in advanced analytics, machine learning, and data engineering.

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Work Culture and Environment

• Hybrid work model offers flexibility to balance on-site collaboration with remote productivity.

• Strong emphasis on collaboration, with regular team meetings, cross-departmental projects, and open communication channels.

• Employee well-being is prioritized through mental health programs, wellness resources, and work-life balance initiatives.

• The company actively promotes diversity and inclusion, ensuring that all employees feel valued and empowered.

Please click here to apply.