American Express – Analyst Data Analytics

Job Description

American Express is hiring talented and analytical professionals for the position of Analyst – Data Analytics within its Global Commercial Services (GCS) division in Gurugram. This opportunity is ideal for candidates who are passionate about data analytics, automation, machine learning, and business intelligence solutions. The role focuses on driving operational efficiency, enabling sales growth, and improving decision-making processes through advanced analytics and automation technologies. As part of Team Amex, candidates will work in a dynamic and innovation-driven environment where data, technology, and business strategy come together to create impactful customer-focused solutions for businesses across the globe.

In this role, professionals will collaborate closely with Sales, Marketing, Technology, Analytics, and Capability teams to design and implement automation solutions for operational processes across multiple US SME channels. The Analyst – Data Analytics position requires strong technical expertise in Python, SQL, Hive, big data technologies, and machine learning techniques. Candidates will work on identifying process gaps, analyzing operational trends, mining large datasets, and building automated analytical solutions that improve business performance and reduce manual intervention. The role also offers exposure to cloud technologies, CRM platforms, visualization tools, and advanced statistical modeling methodologies within a highly collaborative enterprise environment.

This position is particularly suitable for individuals who enjoy solving business problems using data-driven approaches and innovative technologies. American Express values professionals who demonstrate curiosity, analytical thinking, adaptability, and a passion for continuous learning. Employees joining this role will gain hands-on experience working with enterprise-scale data systems, automation frameworks, predictive analytics models, and operational intelligence platforms. The company also provides extensive career development opportunities, leadership training, wellness benefits, and a supportive work culture that encourages employees to innovate, grow professionally, and contribute meaningfully to the future of digital financial services and analytics-driven business transformation.

Roles & Responsibilities

• Design and implement automation solutions for operational processes across various US SME sales and commercial business channels to improve efficiency and scalability.
• Collaborate with stakeholders across Sales, Marketing, Technology, Control Management, Analytics, and Capabilities teams to ensure successful execution of data-driven business initiatives.
• Perform advanced data analysis, data mining, trend identification, and business intelligence reporting using Python, SQL, Hive, PySpark, and related analytical tools.
• Identify operational gaps, inefficiencies, and business challenges through detailed exploratory analysis and recommend data-backed process improvements.
• Develop, validate, and implement automated operational workflows with minimal manual intervention to improve productivity and decision-making accuracy.
• Build machine learning models, statistical analysis frameworks, and predictive analytical solutions to support business growth and operational optimization.
• Work with structured and unstructured datasets in large-scale big data environments to generate actionable insights and improve business performance.
• Create dashboards, visual reports, and analytical presentations using Tableau, Power BI, Excel, Splunk, or other visualization and reporting tools.
• Support data validation, model testing, and performance optimization activities to ensure the reliability and effectiveness of analytical solutions.
• Partner with cross-functional teams to challenge existing processes, introduce innovative approaches, and continuously improve operational systems.
• Utilize CRM tools, workflow platforms, cloud services, and content management systems to streamline business operations and improve collaboration.
• Stay updated with emerging analytics technologies, machine learning trends, big data frameworks, and automation best practices to strengthen technical expertise.

Requirements & Eligibility

• Bachelor’s degree in Data Analytics, Statistics, Economics, Finance, Engineering, Computer Science, Artificial Intelligence, or another quantitative field.
• Strong proficiency in Python and SQL with practical experience in data analysis, automation, scripting, and analytical problem-solving.
• Hands-on experience working with big data environments, including technologies such as Hive, PySpark, Hadoop, Spark, NoSQL databases, or relational databases.
• Knowledge of statistical modeling, machine learning algorithms, data mining techniques, and model validation methodologies for business analytics applications.
• Experience using analytical and visualization tools such as Tableau, Power BI, Splunk, Excel VBA, or similar business intelligence platforms.
• Understanding of cloud technologies and services such as Google Cloud Platform, Azure, or related cloud-based analytics environments.
• Familiarity with CRM tools like Salesforce, workflow management systems, ServiceNow, SharePoint, Confluence, or related enterprise collaboration platforms.
• Strong analytical thinking and problem-solving capabilities with the ability to manipulate, interpret, and derive insights from complex datasets.
• Excellent communication and interpersonal skills with the ability to collaborate effectively across multiple business functions and stakeholder groups.
• Ability to work independently, manage multiple priorities, and deliver high-quality results within dynamic and fast-paced business environments.
• Self-driven mindset with curiosity, innovation-focused thinking, and passion for continuous learning in analytics, automation, and data science technologies.
• Advanced knowledge of Microsoft Office tools including Excel pivot tables, macros, presentation creation, and analytical reporting techniques.

Expected Salary

The expected salary for the Analyst – Data Analytics role at American Express generally ranges between ₹10 LPA to ₹18 LPA depending on technical expertise, analytics experience, machine learning knowledge, and proficiency in big data technologies. Candidates with strong Python, SQL, cloud analytics, and automation skills may receive higher compensation packages along with additional performance-based incentives. Employees also benefit from hybrid work flexibility, wellness programs, leadership development opportunities, comprehensive insurance coverage, and long-term career growth within the global financial services industry.

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