Develop and implement AI and predictive modeling solutions (e.g., B2S Funnel Modelling, OA Penetration, Customer Behavior Models) to drive future growth and improve forecast accuracy
Oversee MLOps practices to ensure scalable, reliable, and sustainable deployment of AI/ML models for operational improvement
Transform large and complex datasets into actionable business intelligence that optimizes operational costs, customer engagement, and growth opportunities
Drive continuous improvement of predictive analytics to enhance forecast accuracy and business planning efficiency
Align AI strategy with business priorities by engaging cross-functional teams to integrate predictive models into decision-making processes
Facilitate capability building for stakeholders to effectively adopt and utilize AI-driven insights
Requirements
Bachelor's degree in Data Science, Statistics, Computer Science, Business Analytics, or related field
5+ years in data science, AI/ML, or advanced analytics,
Proven track record in leading AI/ML projects from ideation to deployment at scale
Exposure to MLOps implementation, predictive modeling, and data-driven business transformation
Advanced expertise in machine learning, deep learning, and AI frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)
Strong background in predictive analytics, natural language processing (NLP), and data engineering concepts
Proficiency in programming languages (Python, R, SQL) and cloud platforms (AWS, GCP, Azure)
Familiarity with MLOps pipelines and model lifecycle management
Understanding of business process automation and AI-driven decision systems
