American Express – Analyst-Data Analytics

Job Description

American Express is hiring for the role of Analyst-Data Analytics in Gurugram as part of its Analytics, Investment and Marketing Enablement (AIM) team under the Global Commercial Services (GCS) Marketing Organization. This opportunity is ideal for candidates passionate about data analytics, artificial intelligence, machine learning, customer analytics, and business intelligence. The AIM team acts as the analytical backbone of the Global Commercial Card business, enabling profitable customer acquisition, retention, and engagement through advanced analytics, AI-driven targeting, and data-powered decision-making. The selected candidate will contribute to large-scale analytics initiatives that directly influence customer retention strategies and business growth across SME segments and multiple marketing channels.

As an Analyst-Data Analytics professional, candidates will work on building analytical models, deriving business insights, and supporting data-driven customer engagement strategies. The role involves collaborating with decision science teams, marketing stakeholders, sales functions, and business leaders to create impactful analytical solutions such as customer prioritization frameworks, predictive triggers, retention models, and AI-powered engagement strategies. Candidates will gain hands-on exposure to technologies such as Python, PySpark, Hive, Scala, Big Data platforms, machine learning techniques, and Generative AI applications within enterprise analytics ecosystems. This position provides a strong foundation for careers in data science, business analytics, AI-driven marketing analytics, and commercial strategy.

Working at American Express offers exposure to one of the world’s most advanced analytics-driven business environments where innovation, collaboration, and customer-centric problem-solving are highly valued. The role requires strong analytical thinking, statistical knowledge, and communication skills to transform complex data into actionable business recommendations. Candidates will contribute to automation initiatives, performance measurement frameworks, and insight generation processes while working with cross-functional global teams. This opportunity is highly suitable for graduates and early-career professionals seeking long-term growth in analytics, machine learning, AI-enabled business intelligence, and enterprise data strategy within a globally recognized financial services organization.

Roles & Responsibilities

1. Develop and enhance analytical models and AI-driven precursors to support customer retention, targeting, and personalized engagement strategies.
2. Collaborate with decision science, marketing, risk management, and sales teams to design data-backed business solutions and customer treatment frameworks.
3. Analyze large datasets to generate actionable business insights that improve customer retention, revenue growth, and marketing effectiveness.
4. Support digital, field, and phone-based marketing programs by measuring campaign performance and identifying growth opportunities.
5. Build analytical solutions such as customer prioritization tiers, triggers, segmentation models, and predictive frameworks for business decision-making.
6. Work with machine learning techniques, statistical methodologies, and AI-powered analytical tools to solve complex business problems.
7. Partner with functional leaders and senior stakeholders to identify opportunities for improving customer engagement and commercial performance.
8. Create reports, dashboards, and analytical presentations to communicate insights effectively to business and leadership teams.
9. Drive automation initiatives and continuously improve analytical frameworks, reporting processes, and operational efficiencies.
10. Apply statistical analysis techniques such as regression, hypothesis testing, KNN, t-tests, and chi-square analysis for business analytics use cases.
11. Collaborate across matrix teams including analytics, technology, business strategy, and external partners to deliver high-quality data solutions.
12. Challenge existing processes, identify innovative analytical approaches, and contribute to business growth through data-driven recommendations.

Requirements & Eligibility

1. Bachelor’s or Master’s degree in Computer Science, Statistics, Mathematics, Engineering, Physics, Data Science, or related quantitative disciplines.
2. 0–2 years of relevant experience in data analytics, business analytics, machine learning, AI, or data science domains.
3. Strong programming skills in Python, Scala, SQL, PySpark, Hive, or related data engineering and analytics technologies.
4. Knowledge of machine learning techniques, statistical modeling, predictive analytics, and AI-powered analytical methodologies.
5. Understanding of statistical concepts such as regression analysis, hypothesis testing, KNN, t-tests, chi-square tests, and probability models.
6. Familiarity with Big Data technologies, data processing frameworks, and large-scale enterprise analytics environments.
7. Strong analytical thinking and problem-solving abilities with capability to derive meaningful insights from complex datasets.
8. Excellent communication and interpersonal skills with the ability to present analytical findings clearly to business stakeholders and leadership teams.
9. Ability to work independently and collaboratively within matrix organizations involving analytics, business, technology, and marketing teams.
10. Understanding of customer analytics, retention analytics, marketing measurement, or commercial business intelligence concepts will be advantageous.
11. Experience working on academic, internship, research, or personal projects involving data science, analytics, AI, or machine learning is preferred.
12. Strong willingness to learn emerging technologies such as Generative AI, advanced analytics frameworks, and enterprise data science solutions.

Expected Salary

The expected salary for the Analyst-Data Analytics role at American Express in Gurugram generally ranges between ₹10 LPA to ₹18 LPA depending on educational background, technical expertise, analytics experience, machine learning skills, and interview performance. Candidates with strong programming knowledge, statistical expertise, and hands-on experience in Python, Big Data, or AI technologies may receive higher compensation packages.

In addition to the base salary, employees may receive performance bonuses, medical insurance, wellness benefits, parental support programs, retirement benefits, hybrid work flexibility, learning opportunities, career development programs, and access to world-class analytics and AI-driven business ecosystems at American Express.

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