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Accenture

Advises businesses and runs their technology

AI Decision Science Consultant - Multiple Teams

Data ScienceConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • At least 4 years of work experience in marketing analytics with a reputed organization.
  • At least 3 years of experience in commerce, data-driven merchandising, or commercial analytics involving pricing, promotions, assortment optimization, personalization or recommendations, route-to-market, or related retail/CPG capabilities.
  • Strong understanding of econometric and statistical modeling, including regression analysis, hypothesis testing, multivariate analysis, time series, and optimization, with ability to apply these techniques to commerce use cases such as pricing, promotions, assortment, demand, and targeting.
  • Expertise in Azure Machine Learning, SQL, R, Python, and PySpark; working experience with large language model application frameworks such as LangChain and LangGraph, retrieval-augmented generation, and vector retrieval.
  • Proficiency in non-linear optimization and resource optimization.
  • Familiarity with design patterns for deploying and maintaining machine learning models in production.
  • Strong command of commerce, marketing, customer, product, pricing, promotion, and transaction data, and corresponding business processes in retail and consumer packaged goods.
  • Hands-on experience with Excel, Word, and PowerPoint for communication and documentation.
  • Bachelor's or Master's degree in Statistics, Economics, Mathematics, Computer Science, or related disciplines.
  • Knowledge of the consumer packaged goods or retail industry.
  • Strong client communication skills.
  • Advanced task management knowledge and experience, including planning tasks, discussing and working on priorities, tracking work, and reporting progress.
  • Working knowledge of resource optimization.
  • Logical thinking and a systematic approach to analyzing data, problems, and situations, including noticing discrepancies and inconsistencies.
  • Strong understanding of customer, product, pricing, promotion, assortment, campaign, and transaction data.
  • Proficiency in Excel, Microsoft Word, and PowerPoint.
  • Strong client communication.

Responsibilities

  • Work through project phases from data discovery and commerce problem definition through model and agent building, validation, integration, deployment, and handover.
  • Define data requirements for SONG Commerce analytics and Agentic Commerce capabilities.
  • Clean, aggregate, analyze, and interpret data, and carry out data quality analysis.
  • Apply market sizing, lift estimation, and experimentation and measurement approaches to pricing, promotions, campaigns, personalization, and other commerce decisions.
  • Apply non-linear optimization techniques to pricing, promotion, assortment, offer, and resource-allocation use cases.
  • Use time-series, clustering, causal, and descriptive analytics to support merchandising and commerce intelligence, including demand, pricing, promotion, assortment, and customer/product decisioning.
  • Apply state space modeling and mixed effect regression.
  • Develop and validate AI/ML models in Azure Machine Learning and integrate model outputs into commerce decisioning and agentic workflows.
  • Develop and manage data pipelines.
  • Use knowledge of scalable machine learning architecture design patterns and tools for deploying and maintaining machine learning models in production, including cloud platforms for pipelining, deployment, and scaling elasticity models.
  • Design retrieval, tool-calling, and agentic workflows for commerce use cases using natural language processing, large language models, LangChain/LangGraph, and retrieval-augmented generation, with appropriate grounding, guardrails, and evaluation.
  • Manage client relationships and expectations and communicate insights and recommendations effectively.
  • Contribute to capability building and reusable assets for AI-enabled and Agentic Commerce.
  • Manage client expectations and develop trusted relationships.
  • Maintain strong communication with key stakeholders.
  • Advise clients on data-driven commerce decisions and translate analytical and agentic outputs into practical pricing, promotion, assortment, personalization, and customer-action recommendations.

Desired Qualifications

  • Preferred advanced degrees include M.Tech, M.Phil, or Ph.D. in Statistics, Econometrics, or a related field from reputed institutions.
  • AWS cloud capability.
  • Scalable machine learning architecture design patterns.
  • AI capability building.
  • React or Angular frontend development.
  • DevOps pipelines.
  • Conversational AI.
  • Agent observability and evaluation.
  • Model and prompt governance.
  • Integration of agentic workflows with commerce, CRM, marketing, and campaign platforms.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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