Senior Analyst, Data Governance & Management

American Express

. Develop, review, and maintain data capabilities supporting customer management and risk models, including datasets used for model development, execution, and ongoing performance monitoring.

Posted 10/9/2026full-timeBengaluru • IndiaSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in data analysis, management, and governance, with a strong ability to translate complex datasets into actionable business insights. Proficient in utilizing BigQuery and Python for data processing and automation, while effectively communicating findings to diverse stakeholders.

Highest-signal resume keywords

BigQueryPythonData AnalysisData GovernanceAnalytical Problem-Solving

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Data ManagementData QualitySQLMachine LearningModel DevelopmentData Lifecycle ManagementAutomated Data ProcessesData LineageData CapabilitiesPerformance Monitoring

Soft Skills

Strong CommunicationTeam CollaborationOwnershipIndependent WorkAnalytical Thinking

Certifications & Qualifications

MBAMaster's Degree in EconomicsMaster's Degree in StatisticsMaster's Degree in Computer ScienceMaster's Degree in Data Science

Industry Keywords

Financial ServicesPaymentsCredit RiskFraud RiskCustomer Analytics

Tech Stack

Tools & technologies

BigQueryPythonSQL

About the role

Key responsibilities & impact

Develop, review, and maintain data capabilities supporting customer management and risk models, including datasets used for model development, execution, and ongoing performance monitoring.
Analyze large and complex datasets to identify meaningful patterns, trends, data quality issues, and opportunities for improvement.
Identify opportunities to automate manual processes, simplify existing workflows, and improve operational efficiency.
Identify opportunities to optimize data capabilities and reduce unnecessary storage, processing, and maintenance costs.
Explore innovative approaches across data, analytics, automation, and machine learning to continuously improve existing capabilities.
Partner with cross-functional teams across risk, analytics, technology, and other business areas to improve data accessibility, quality, governance, and usability.
Structure and clearly communicate analytical findings, recommendations, risks, and business impact to leadership and key stakeholders.
Navigate complex and unstructured problems by asking thoughtful questions, evaluating different approaches, and translating findings into actionable solutions.

Requirements

What you’ll need

MBA or Master's degree in Economics, Statistics, Computer Science, Data Science, or a related quantitative field.
0–30 months of relevant experience in analytics, data management, data governance, or related data capabilities.
Working knowledge of BigQuery and Python, with the ability to analyze and work with large datasets.
Understanding of data analysis concepts and the ability to translate data into meaningful business insights.
Ability to manage project deliverables and drive initiatives toward measurable business outcomes.
Strong analytical and problem-solving skills, with the ability to work through complex and unstructured problems.
Ability to work independently and take ownership of assigned deliverables while contributing effectively within a team environment.
Strong written and verbal communication skills, with the ability to clearly communicate findings to both technical and non-technical stakeholders.
Hands-on experience with BigQuery, Python, SQL, or similar data and analytical technologies.
Experience developing or supporting automated data processes and workflows.
Exposure to data governance, data quality, metadata management, data lineage, or data lifecycle management.
Understanding of model development, model performance monitoring, or the data requirements associated with analytical and machine learning models.
Exposure to financial services, payments, credit risk, fraud risk, or customer analytics.
Offer of employment is conditioned upon successful completion of a background verification check, subject to applicable laws and regulations.

Benefits

Comp & perks

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