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Data Science Architect

4 weeks ago

Bengaluru, India LTIMindtree Full time

Role and Responsibilities


Domain - CPG & Retail / Hi tech / Lifesciences/ Oil and gas / Manufacturing


Location - Bangalore/Pune/ Mumbai/Chennai/Kolkata


Experience Required - 12 years to max 16 years


Responsibilities


  • 12+ years of overall experience, with 8+ years in AI, ML, and data science-focused roles, and 5+ years specifically in implementing or consulting for CPG & Retail.
  • Develop AI/ML models for price elasticity, marketing – mix / marketing spend optimization, demand forecasting, inventory optimization, predicting out – of – stock, estimating lost sales, B2C pricing strategies, and personalized customer experiences in CPG & Retail sectors.
  • Leverage data from point-of-sale systems, customer behavior analytics, and supply chain operations to create data-driven solutions that enhance operational efficiency and boost profitability.
  • Implement AI-driven recommendation systems to optimize product assortment, upselling, and cross-selling, next – best offer strategies in retail environments.
  • Use advanced analytics to identify trends, customer segments, and buying behaviors, driving targeted marketing campaigns and customer retention programs.
  • Apply machine learning algorithms for predictive analytics in sales forecasting, shelf space optimization, and supply chain management.
  • Collaborate with cross-functional teams, including marketing, sales, supply chain, product managers, and domain experts, to define and implement AI/ML strategies that align with organizational goals.
  • Lead pre-sales efforts by consulting with clients, understanding their specific business needs in the CPG & Retail space, and developing customized AI solutions.
  • Drive research and development of innovative AI applications to solve complex business challenges, such as using AI/ML for product demand forecasting, price optimization, consumer sentiment analysis, and operational efficiency.
  • Lead and mentor teams in building Proof of Concepts (POCs) and production-ready AI/ML systems for various clients in the CPG & Retail industry.
  • Document technical artifacts and establish best practices for deploying AI/ML systems on cloud platforms (AWS, Azure, GCP) and implementing Python libraries specific to CPG & Retail.
  • Engage directly with clients to communicate complex AI scenarios in CPG & Retail and provide strategic recommendations for improving sales, reducing waste, and enhancing customer experiences.
  • Ensure AI solutions adhere to quality, ethical, and compliance standards while optimizing performance for reliability and efficiency in production environments.
  • Spearhead change management processes to facilitate the integration of AI technologies into existing business systems, such as CRM, ERP, and supply chain systems.
  • Share knowledge and mentor team members to enhance their expertise in generative AI, advanced data science techniques, and their application in the CPG & Retail industry.



Skills


  • Strong communication skills with experience managing various stakeholder relationships in CPG & Retail to gain consensus on complex technical solutions.
  • Deep understanding of the CPG & Retail landscape, including product lifecycle management, merchandising strategies, customer behavior, and supply chain optimization.
  • Experience in architecting AI/ML solutions that address challenges like demand forecasting, dynamic pricing, inventory management, and customer segmentation in the CPG & Retail space.
  • Proficiency in Python with experience analyzing CPG & Retail data (e.g., transaction data, consumer behavior, sales data, and third – party syndicated datasets like Nielsen and IRI and make sense of them towards predictive modeling) [SM1] and providing strategic recommendations using AI/ML techniques.
  • Mastery of AI frameworks and generative models, including Transformers (GPTs, BERT, LLaMa, etc.), with practical applications in CPG & Retail, such as generating personalized product recommendations and optimizing promotional strategies.
  • Expertise in machine learning techniques (CNN, RNN, k-NN, Naive Bayes, SVM, Decision Forests) and practical experience in NLP, time-series forecasting, and recommendation systems for retail.
  • Advanced knowledge of cloud platforms like Amazon SageMaker, Azure ML Studio, GCP BigQuery, and industry-specific platforms like SAP HANA, Salesforce, and Oracle Retail.
  • Strong math skills, including statistics and algebra, with an analytical mindset and business acumen for solving CPG & Retail-specific problems, such as optimizing pricing strategies or forecasting demand.
  • Experience with data science libraries and frameworks, including TensorFlow, Keras, PyTorch, and Pandas, with deep expertise in deploying models for omnichannel retail environments.
  • Publications or contributions to AI/ML conferences, journals, or open-source communities, particularly in the CPG & Retail or eCommerce domains.
  • Relevant certifications in AI/ML at the Architect/Lead level, with a Ph.D. or master’s degree in computer science, Data Science, or related fields.