{"id":1134386,"url":"https://alion.io/job/american-express-senior-analyst-data-science-3","title":"Senior Analyst-Data Science","company":{"id":2209,"name":"American Express","domain":"americanexpress.com","url":"https://alion.io/company/american-express","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Oracle","truth_index":{"grade":"A","score":98,"open_postings":39,"ghost_share":0.051,"stale_share":0.077,"repost_share":0.154,"time_to_fill_p50_days":7,"computed_at":"2026-10-03T05:45:00Z"}},"role":"Analytics","role_family":"Analytics","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Gurgaon, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":16500,"max_usd":33000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":16},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"DSPy","optional":false},{"name":"Embeddings","optional":false},{"name":"Function Calling","optional":false},{"name":"Git","optional":false},{"name":"LangChain","optional":false},{"name":"LlamaIndex","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"pySpark","optional":false},{"name":"Python","optional":false},{"name":"RAG","optional":false},{"name":"Semantic Search","optional":false},{"name":"Semantic Search","optional":false},{"name":"SQL","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Hallucination","optional":true},{"name":"Spark","optional":true}],"status":"closed","first_seen_at":"2026-09-23T04:29:42Z","employer_posted_date":"2026-09-23","last_verified_at":"2026-10-01T01:59:22Z","board_verified":false,"closed_at":"2026-10-01T01:59:22Z","days_open":7,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":7},"description":"The AIM (Analytics, Investment & Marketing Enablement) team - a part of GCS Marketing - is the analytical engine that enables the Global Commercial Services portfolio of American Express. Accelerating growth momentum, increasing profitability, and strengthening our value proposition are key objectives for this organization.\nThis Senior Analyst - Data Science role, based out of India, will join the Prospect Cross-functional team within AIM and execute analytical workstreams supporting prospect targeting and acquisition initiatives. Leveraging a broad analytical toolkit-including advanced machine learning, predictive modeling, optimization, and Generative AI-the role supports the end-to-end development of scalable analytical solutions that enhance targeting precision, engagement effectiveness, and marketing ROI.\nThis role provides an opportunity to build next-generation AI-powered capabilities across prospect enrichment, intelligent targeting, lead prioritization, and decision support by combining advanced analytics with modern Generative AI techniques. Working closely with data scientists, product managers, engineers, and business stakeholders, the Analyst will develop scalable analytical solutions that accelerate data-driven decision making while maintaining the highest standards of Responsible AI and model governance.\nShift Time- 1:30 PM - 9:30 PM IST\n Execute analytical and data science solutions to solve business problems using statistical techniques, machine learning, and modern GenerativeAI approaches.\n\nDevelop, test, and maintain analytical models and AI-enabled data products-including predictive models, prospectscoring,prioritization, matching, enrichment, and intelligent decision-support capabilities-to improve targeting and acquisition effectiveness.\n\nDesign, build, and evaluate Generative AI workflows, including Retrieval-Augmented Generation(RAG), embedding-based retrieval, semanticsearch, prompt engineering, structured outputs, and LLM-powered applications, selecting appropriate approaches based on business requirements, solution quality, scalability, latency, cost, and governance considerations.\n\nDesign and execute experiments to evaluate prompting strategies, retrieval configurations, model selection, and workflow architectures, continuously optimizing solution quality, response accuracy, operational efficiency, and business impact.\n\nPerform data extraction, preparation, feature engineering, and data quality validation using large-scale datasets to support AI/ML model development andanalytical initiatives.\n\nApply statistical and machine learning techniques to improve model performance through experimentation, feature refinement, validation, and continuousmodel optimization using established best practices.\n\nCollaborate with product, engineering, and business stakeholders to support the implementation, deployment, monitoring, andcontinuous improvement of analytical and Generative AI solutions within business workflows.\n\nEvaluate AI and GenAI solution performance using quantitative and qualitative evaluation techniques, including model performance metrics, retrieval quality, response accuracy, prompt robustness, business outcome measures, and production monitoring.\n\nCommunicate analytical findings, model outputs, and business insights clearly through presentations and technical documentation for both technical andnon-technical stakeholders.\n\nEnsure compliance with Responsible AI principles, model governance, dataintegrity, explainability, biasassessment, promptsafety, monitoring, audit readiness, and enterprise risk management standards throughout the analytical development lifecycle.\n\n Degree in a quantitative field preferred, such as Engineering, Mathematics, Computer Science, Finance, Economics, Statistics, or a related discipline.\n\n2+ years of experience in data science, advanced analytics, machine learning, decision science, or related quantitative roles.\n\nStrong programming skills in Python and SQL, with working knowledge of Hive and/or PySpark in large-scale data environments, hands-on experience developing machine learning models end-to-end, and familiarity with software engineering best practices including Git-based version control.\n\nDemonstrated hands-on experience building or experimenting with LLM-based applications, including Retrieval-Augmented Generation (RAG), prompt engineering, semantic search, embeddings, structured outputs, or AI-powered assistants.\n\nKnowledge of supervised machine learning techniques (e.g., gradient boosting, tree-based models, regression, clustering) and statistical techniques suchas hypothesis testing, multivariate testing, ANOVA, and model evaluation methodologies.\n\nExposure to AI agent frameworks, tool/function calling, vector databases, LLM orchestration frameworks (e.g., LangChain, LlamaIndex, DSPy), context management, or workflow automation is a plus.\n\nFamiliarity with modern ML/AI development frameworks, open-source libraries, prompt lifecycle management, and evaluation frameworks.\n\nStrong analytical and problem-solving skills, with the ability to execute well-defined analytical tasks accurately and efficiently.\n\nDemonstrated ability to manage assigned work independently while collaborating effectively within a cross-functional team.\n\nHigh attention to detail, intellectual curiosity, and an experimentation mindset with the ability to evaluate solutions objectively and iterate based on evidence.\n\nStrong written and verbal communication skills, with the ability to clearly explain analytical findings and support stakeholder discussions.\n\nFamiliarity with Responsible AI principles, including explainability, bias and fairness assessment, hallucination mitigation, prompt safety, model monitoring, evaluation, audit readiness, and GenAI risk management practices.","description_format":"text","description_chars":5822,"description_truncated":false,"requirements":{"experience_years_min":2,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":[],"hiring_locations":[{"name":"India","iso":"IN","kind":"country"}],"hiring_excludes":[],"relocation_offered":false,"industries":["Commercial & Retail Banks","Cards & Card Issuing","Payment Processing & Gateways"],"lifecycle":[{"event":"open","at":"2026-09-23T06:57:17Z"},{"event":"close","at":"2026-10-01T01:59:22Z"}],"visa":[],"liveness":null,"pay":null,"html_url":"https://alion.io/job/american-express-senior-analyst-data-science-3","json_url":"https://alion.io/job/american-express-senior-analyst-data-science-3.json","meta":{"generated_at":"2026-10-04T01:48:19Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":2447,"day_limit":5000,"remaining_today":2553,"minute_limit":60,"resets_at":"2026-10-05T00:00:00Z"}}}