Ankit Sharma

Role Focus: AI architecture, strategy, and technical leadership

• Architected the AI-based Career Recommendation Platform, mapping student skills, interests, and outcomes to optimal learning and job paths.
• Designed end-to-end ML pipelines for the Student Performance & Dropout Risk Prediction System, enabling early intervention.
• Built production-grade workflows for data ingestion, feature engineering, training, evaluation, and deployment.
• Established internal standards for data quality, model governance, and iteration cycles.
• Mentored junior engineers and analysts on ML system design and production best practices.
• Enabled leadership to plan batches and resources using forward-looking intelligence instead of static reports.
• Drove the shift from reactive reporting to AI-led, KPI-driven decision systems across operations.

Role Focus: Predictive intelligence and business modeling

• Developed the Student Performance & Dropout Risk Prediction System, improving student retention by 20–30%.
• Built the Enrollment Forecasting & Batch Optimization Engine used for capacity planning and faculty allocation.
• Designed experimentation frameworks for course structure, curriculum impact, and pricing strategy.
• Created personalized learning-path recommendations that later evolved into the AI career engine.
• Improved batch utilization and faculty planning efficiency by 25–35% using predictive planning.
• Shifted analytics from “what happened” to “what will happen and what to do next.”

Role Focus: Transition from analytics to applied machine learning

• Built first production ML models for student performance and engagement prediction.
• Converted business KPIs into features and training datasets using Python and SQL.
• Prototyped early dropout-risk scoring used by academic teams for intervention.
• Introduced model evaluation practices and baseline experimentation.
• Bridged reporting workflows with predictive systems, laying the foundation for the data science function.

Role Focus: Business intelligence and operational visibility

• Built the Admissions & Marketing Analytics Engine using SQL and Python.
• Created the Executive KPI & Decision Intelligence Dashboard Suite for center-wise performance, revenue, and instructor effectiveness.
• Performed cohort and funnel analysis to identify dropout patterns and growth bottlenecks.
• Delivered marketing insights that increased lead-to-admission conversion by 18–25%.
• Cut reporting turnaround time from days to minutes, enabling weekly KPI-driven decisions.
• Enabled leadership to move from intuition-based planning to data-led execution.

Role Focus: Core systems, automation, Python-based backend engineering

• Designed and built the Student Management & Operations Platform using Python and MySQL.
• Developed backend services for admissions, fee tracking, batch allocation, certification, and attendance workflows.
• Implemented role-based access for admins, faculty, and operations staff.
• Automated manual processes across enrollment and academic operations.
• Reduced administrative workload and data errors significantly through systemization.
• Built the technical foundation that enabled expansion from 1 center to 4+ centers.