I&F Decision Sci Practitioner Analyst

Skill required: Delivery - Audience Segmentation

Designation: I&F Decision Sci Practitioner Analyst

Qualifications:Any Graduation

Years of Experience:3 to 5 years

Intelligent Operations centers. Our 784,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries.

What would you do Intelligent Operations centers. We embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities. .We re the global managed services arm of Accenture Interactive. We sit in the Operations Business to take advantage of the industrialized run capabilities leveraging investments from Accenture Operations.Our quest is to activate the best experiences on the planet by driving value across every customer interaction to maximize marketing performance. We combine deep functional and technical expertise to future-proof our client s business while accelerating time-to-market and operating efficiently at scale.We are digital professionals committed to providing innovative, end-to-end customer experience solutions focusing on operating marketing models that help businesses transform and excel in the new world, with an ecosystem that empowers our clients to implement the changes necessary to support the transformation of their businesses.You will take ownership of end-to-end campaign analytics workstreams for global clients - from data science modeling, AI/ML deployment and segmentation to measurement and insight generation. Designs, builds and deploys machine learning models and advanced analytics use cases that power the growth analytics strategy for the CRM & Loyalty engagement.

What are we looking for Advanced SQL, campaign analytics and CRM/customer analytics skillsProficiency in Python for machine learning and data science scikit-learn, XGBoost, LightGBM or equivalentExperience building and deploying classification, regression and ranking models at scaleStrong understanding of customer analytics methodologies: propensity modelling, CLTV, churn prediction, predictive segmentationFamiliarity with MLOps practices model monitoring, versioning, lifecycle governance and reproducibilityExperience working with CRM and marketing data: SFMC event data, CDP profiles, transactional and engagement signalsUnderstanding of experimental design, control group methodology and A/B testing statistical frameworksExperience with AI/ML-driven personalization and decision enginesProficiency in Power BI and/or Tableau for dashboard developmentHands-on experience with CRM and campaign platforms (Salesforce Marketing Cloud, Adobe Campaign, Braze, or similar)Strong knowledge of segmentation methodologies and customer analytics (RFM, CLV, propensity scoring)Experience designing campaign measurement frameworks including attribution and incrementality A/B testing, attribution basics and funnel analysisStrong communication skills - ability to translate complex model outputs into clear business recommendationsExperience with agentic AI frameworks and LLM-integrated analytics pipelinesFamiliarity with Salesforce Einstein Analytics and Data Cloud ML capabilitiesKnowledge of Tealium CDP data structures and customer profile attributesCertifications in machine learning or cloud ML platforms (AWS SageMaker, GCP Vertex AI or similar)24 years in data science, machine learning or advanced analytics and 1+ years in campaign analytics or CRM analytics.Proven track record building and deploying predictive models in production environmentsExperience in CRM analytics, loyalty analytics, customer lifetime value modelling or marketing scienceExposure to automobile, airline, retail, FMCG or beauty industryBachelor s or Master s degree in Data Science, Statistics, Computer Science, Mathematics or related field

Roles and Responsibilities: Design and build ML models for assigned use cases - including propensity scoring, churn prediction, next-best-action modelling, CLTV prediction and loyalty tier migration forecastingOwn the full model lifecycle: problem framing, feature engineering, model development, validation, deployment and ongoing performance monitoringPartner with Data Analysts and Analytics Managers to productionise models and integrate outputs into CRM journeys and campaign workflowsContribute to the group-level data science framework - methodology standards, model lifecycle governance and MLOps practicesDesign and govern the global control group framework and statistical methodology across marketsTranslate model outputs into actionable audience briefs and campaign recommendations in partnership with Insights ManagersDocument model methodology, assumptions, performance benchmarks and deployment guidelines for client and internal reviewConduct CLV, churn, and engagement analyses to identify high-value customer segments and at-risk cohortsAnalyze audience, channel, content, conversion, booking, revenue and customer journey performancePrepare insight narratives, drivers of performance and optimization recommendationsLead test-and-learn design (A/B tests, hold-out groups) and interpret results to inform future campaign strategyBuild and maintain campaign performance dashboards that provide real-time and retrospective views of marketing effectiveness

Qualification Any Graduation