Senior Analyst-Data Science

American Express
Gurugram, Bengaluru
Workplace: HybridFull timeFunction: Data Science & Machine LearningExperience: 2-3 yearsEducation: bachelorsSkills: ["Analytical and problem-solving","Independent work","Collaboration","Attention to detail","Clear communication"]

Drive data-driven strategies by designing, developing, and operationalizing predictive and explanatory ML/AI solutions for Sales portfolio performance. Apply machine learning, NLP, and generative AI to build analytics frameworks, forecasting, anomaly detection, and LLM-enabled feature generation. Partner with cross-functional teams to translate business questions into measurable KPIs, create reproducible workflows, and communicate actionable insights to technical and non-technical stakeholders.

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FursaFursa
American Express
American Express
2 days ago

Senior Analyst-Data Science

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Source: Company careers pageValidated by: Fursa AI
Last checked: 10 hours agoStatus: Live

Job Summary

Drive data-driven strategies by designing, developing, and operationalizing predictive and explanatory ML/AI solutions for Sales portfolio performance. Apply machine learning, NLP, and generative AI to build analytics frameworks, forecasting, anomaly detection, and LLM-enabled feature generation. Partner with cross-functional teams to translate business questions into measurable KPIs, create reproducible workflows, and communicate actionable insights to technical and non-technical stakeholders.
Location: Gurugram, Bengaluru
Workplace: Hybrid
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design, develop, and deploy predictive and explanatory ML models to address business problems, including forecasting and anomaly/gaming behavior detection.
  • •Generate actionable sales and client behavior insights using hypothesis testing and well-documented, reproducible analytical workflows.
  • •Contribute to GenAI-enabled analytics solutions, including defining success metrics, monitoring frameworks, and validation approaches (e.g., human-in-the-loop, hallucination detection).
  • •Develop, evaluate, and iterate models using modern ML frameworks with attention to performance, scalability, and interpretability.
  • •Collaborate with cross-functional stakeholders and communicate analytics findings and KPI progress to technical and non-technical audiences, including executive-level updates.

Pay and Benefits

Perks:Health InsuranceDentalVisionLife InsuranceDisability InsuranceParental LeaveRetirementWellness StipendCounseling Support

Key Requirements

  • •2–3 years of relevant experience in data science, analytics, or a related quantitative field.
  • •Bachelor’s degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering, Economics).
  • •Translate complex business problems into quantitative analytical frameworks and models, with strong analytical problem-solving skills.
  • •Apply machine learning using standard libraries (e.g., scikit-learn, TensorFlow, PyTorch) and handle NLP tasks such as text classification, summarization, or information extraction.
  • •Strong proficiency in Python and SQL; familiarity with distributed processing (e.g., Spark), cloud data platforms (GCP/AWS/Azure), and data visualization tools (matplotlib, seaborn, Tableau).
Experience:2-3 years
Education:Bachelor's in quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering, Economics)
Skills:Analytical and problem-solvingIndependent workCollaborationAttention to detailClear communication
Tech Stack:Machine learningNLPGenerative AILLMTensorFlowPyTorchScikit-learnText classificationSummarizationInformation extractionPythonSQLSparkGCPAWSAzureBigQueryMatplotlibSeabornTableau

Company Brief

American Express
Provides global payment, credit, and travel-related financial services for consumers and businesses. Best known for its charge and credit cards, merchant payment network, and premium customer rewards and servicing.
Industry: Payments
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: New York City, United States
Founded: 1850
WebsiteLinkedIn