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Larsen & Toubro Infotech Ltd (LTI) is seeking a Senior Specialist - Architecture Data Scientist to design and develop data-driven solutions for ecommerce marketing analytics, customer behavior, and decision automation. The role focuses on product segmentation, marketing performance attribution, trend detection, and automated decision systems.
The candidate will build clustering/classification models, develop multitouch attribution, forecasting, and productionize ML models within cross-functional
Senior Specialist - Architecture JD Job Description Data Scientist Job Overview We are looking for an experienced Data Scientist to design and develop datadriven solutions that help the business improve customer understanding marketing effectiveness trend identification and decisionmaking The ideal candidate will combine strong data science and machine learning expertise with a good understanding of ecommerce marketing analytics customer behavior and business decision automation
Product Segmentation Develop datadriven approaches to segment products based on customer behavior sales patterns product attributes profitability and market performance Build clustering and classification models to identify meaningful product segments Identify product affinities crosssellupsell opportunities and product lifecycle patterns Develop segmentation strategies that support pricing promotions merchandising and portfolio decisions
Marketing Performance Attribution Develop attribution models to measure the effectiveness and ROI of different marketing and publicity activities Analyze marketing performance across ecommerce platforms digital channels traditional marketing advertising and publicity campaigns Identify the contribution of individual marketing channels campaigns and touchpoints to customer acquisition conversion and revenue Build multitouch attribution and incrementality models where appropriate Provide insights to optimize marketing spend and improve campaign effectiveness
Trend Detection Develop statistical and machine learning models to identify emerging trends anomalies and changes in customer and product behavior Analyze sales customer market and marketing data to identify early indicators of emerging opportunities or risks Build forecasting and timeseries models to predict demand sales customer behavior and market trends Develop automated s and monitoring mechanisms for significant changes in business metrics
Decision Automation Develop predictive and prescriptive analytics solutions that enable automated or semiautomated business decisions Identify business processes where datadriven decisions can replace or augment manual decisionmaking Develop recommendation optimization and rulesMLbased decision engines Collaborate with business stakeholders to define decision criteria expected outcomes and measurable KPIs Productionize models and integrate them into business applications and workflows
Analyze large and complex datasets to identify trends patterns relationships and actionable insights Develop train validate and optimize machine learning and statistical models Perform exploratory data analysis feature engineering data preprocessing and model evaluation Develop predictive classification clustering recommendation forecasting attribution and optimization models Translate complex business problems into analytical and machine learning solutions Collaborate with business marketing product data engineering and technology teams Deploy and monitor machine learning models in production environments Communicate analytical findings and recommendations effectively to both technical and nontechnical stakeholders Establish appropriate model performance metrics and continuously improve models based on business outcomes Ensure data quality model accuracy scalability explainability and responsible use of AIML solutions
Experience 10 years of experience in Data Science Machine Learning Marketing Analytics or a related field Strong programming skills in Python with experience using Pandas NumPy Scikitlearn TensorFlow or PyTorch Strong understanding of statistics probability machine learning and model evaluation Experience with customerproduct segmentation marketing analytics attribution modeling trend detection forecasting or decision automation Strong SQL skills and experience working with large datasets Experience with supervised and unsupervised learning techniques including regression classification clustering and timeseries modeling Experience with data visualization and analytical tools such as Power BI Tableau or Python visualization libraries Experience with at least one major cloud platform such as AWS Azure or Google Cloud Understanding of ML deployment APIs MLOps and model lifecycle management Strong analytical problemsolving and communication skills
Experience in ecommerce retail consumer products marketing or digital analytics Experience with marketing attribution and measurement frameworks Knowledge of customer journey analytics and multitouch attribution Experience with recommendation systems and personalization Experience with Generative AI LLMs NLP