Join Accenture as a Senior Analyst in I&F Decision Science. This full-time role involves leveraging AI and data science to drive innovative solutions for global clients. You will be instrumental in transforming businesses by unlocking the power of AI and data across various facets.

Accenture is a leading professional services company renowned for its expertise in digital, cloud, and security. We empower clients across over 40 industries with Strategy and Consulting, Technology, and Operations services. Our extensive network of Advanced Technology and Intelligent Operations centers, powered by 784,000 professionals, delivers on the promise of technology and human ingenuity daily, serving clients in more than 120 countries.

As part of Accenture Interactive's global managed services arm, we operate within the Operations Business, utilizing industrialized run capabilities. Our mission is to create exceptional customer experiences by maximizing marketing performance and driving value across every interaction. We combine deep functional and technical expertise to future-proof client businesses, accelerate time-to-market, and operate efficiently at scale. We are digital professionals dedicated to delivering innovative, end-to-end customer experience solutions, focusing on operating marketing models that enable businesses to excel in the modern landscape.

Take ownership of end-to-end campaign analytics workstreams for global clients, encompassing data science modeling, AI/ML deployment, segmentation, measurement, and insight generation.

Design, build, and deploy machine learning models and advanced analytics use cases to support CRM and Loyalty engagement growth strategies.

Develop and implement ML models for various use cases, including propensity scoring, churn prediction, next-best-action modeling, CLTV prediction, and loyalty tier migration forecasting.

Manage the complete model lifecycle, from problem framing and feature engineering to model development, validation, deployment, and ongoing performance monitoring.

Collaborate with Data Analysts and Analytics Managers to productionize models and integrate their outputs into CRM journeys and campaign workflows.

Contribute to the group-level data science framework, focusing on methodology standards, model lifecycle governance, and MLOps practices.

Design and govern the global control group framework and statistical methodology across different markets.

Translate model outputs into actionable audience briefs and campaign recommendations in partnership with Insights Managers.

Document model methodology, assumptions, performance benchmarks, and deployment guidelines for both client and internal review.

Conduct CLV, churn, and engagement analyses to identify high-value customer segments and at-risk cohorts.

Analyze audience, channel, content, conversion, booking, revenue, and customer journey performance to derive actionable insights.

Prepare insight narratives, identify key performance drivers, and provide optimization recommendations.

Lead test-and-learn design, including A/B tests and hold-out groups, and interpret results to inform future campaign strategy.

Build and maintain campaign performance dashboards that offer real-time and retrospective views of marketing effectiveness.

We are seeking a Senior Analyst with expertise in Delivery - Audience Segmentation, backed by 5-8 years of experience.

Required proficiency includes advanced SQL, campaign analytics, and CRM/customer analytics. You must be skilled in Python for machine learning and data science, utilizing libraries like scikit-learn, XGBoost, or LightGBM.

Demonstrated experience in building and deploying classification, regression, and ranking models at scale is essential. A strong understanding of customer analytics methodologies such as propensity modeling, CLTV, churn prediction, and predictive segmentation is crucial.

Familiarity with MLOps practices, including model monitoring, versioning, lifecycle governance, and reproducibility, is expected. Experience working with CRM and marketing data, including SFMC event data, CDP profiles, transactional, and engagement signals, is required.

Possess a solid understanding of experimental design, control group methodology, and A/B testing statistical frameworks. Experience with AI/ML-driven personalization and decision engines is also necessary.

Proficiency in Power BI and/or Tableau for dashboard development is required. Hands-on experience with CRM and campaign platforms like Salesforce Marketing Cloud, Adobe Campaign, or Braze is a plus.

Strong knowledge of segmentation methodologies and customer analytics (RFM, CLV, propensity scoring) is vital. Experience designing campaign measurement frameworks, including attribution and incrementality, A/B testing, and funnel analysis, is necessary.

Excellent communication skills are required to translate complex model outputs into clear business recommendations. Experience with agentic AI frameworks and LLM-integrated analytics pipelines is advantageous.

Familiarity with Salesforce Einstein Analytics and Data Cloud ML capabilities, along with knowledge of Tealium CDP data structures and customer profile attributes, is beneficial. Certifications in machine learning or cloud ML platforms such as AWS SageMaker or GCP Vertex AI are a plus.

Candidates should have 2-4 years in data science, machine learning, or advanced analytics, with at least 1 year in campaign analytics or CRM analytics. A proven track record of building and deploying predictive models in production environments is essential.

Experience in CRM analytics, loyalty analytics, customer lifetime value modeling, or marketing science is required. Exposure to the automobile, airline, retail, FMCG, or beauty industry is preferred.

Candidates must possess a Bachelor's or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related field.