Data Analytics Analyst

American Express

. Drive sentinel analytics across channels and Amex product offerings.

Posted 9/21/2026full-timeGurugram • IndiaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in statistical and machine learning techniques to drive analytics and business insights, with a strong focus on AI and GenAI methodologies. Proficient in project management and cross-functional collaboration to deliver impactful data-driven solutions.

Highest-signal resume keywords

Statistical AnalysisMachine Learning TechniquesSQL ProficiencyPython ProgrammingProject Management

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Data Mining TechniquesRegression AnalysisClusteringDecision TreesXGBoostK-MeansAnalytical SolutionsBusiness Problem SolvingEmerging AI TechniquesDigital Analytics

Soft Skills

Strong Communication SkillsInterpersonal SkillsAnalytical ThinkingConceptual ThinkingCollaboration

Industry Keywords

Sentinel AnalyticsGaming PreventionCommercial AcquisitionsCustomer Journey OptimizationSemantic ModelingAutomated InsightsBackground Verification

Tech Stack

Tools & technologies

PythonSQL

About the role

Key responsibilities & impact

Drive sentinel analytics across channels and Amex product offerings.
Develop innovative analytical solutions and strategies for gaming prevention and profitable commercial acquisitions.
Design and create prospect marketing analytics using machine learning and advanced methodologies.
Leverage data science to quantify value, derive insights, and create positive business impact.
Collaborate cross-functionally with channel owners, business partners, data science solution users, and technology partners.
Explore data mining techniques, including regression analysis, clustering, and decision trees.
Integrate emerging AI and GenAI techniques, including customer journey optimization, semantic modeling, and automated insights.
Resolve issues, identify opportunities, define success metrics, and execute initiatives.
Prioritize efforts around the most impactful opportunities.

Requirements

What you’ll need

Bachelor's in engineering or Master’s degree in a quantitative field (e.g., Statistics, Engineering, Physics, Mathematics and Economics) or PhD is required.
Proficiency and experience applying statistical and machine learning techniques to business problems.
Ability to leverage external thinking from academia and/or other industries to develop data science solutions.
Strong communication and interpersonal skills.
Strong analytical/conceptual thinking acumen to solve business problems and articulate key findings to senior leaders/stakeholders succinctly.
Ability to project-manage effectively and manage several concurrent projects through collaboration across teams/geographies.
Familiarity and interest in emerging AI and Gen AI capabilities, with LLM and RAG exposure preferred.
Experience building ML models such as XGBoost and K-Means, with proficiency in SQL, Python, or similar preferred.
Knowledge of digital analytics or experimentation frameworks is a plus.
Ability to learn and quickly adapt around the evolving analytics landscape preferred.
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