Swadheen Jain

Strategic AI & Agentic Intelligence Leader delivering enterprise-scale transformation programs for global clients.

Key Contributions & Impact

• Led process mining–led transformation initiatives using Celonis EMS, enabling discovery, execution, and optimization across 60+ clients from insurance, Banking and financial services value chains.
• Architected and delivered AI-augmented process intelligence solutions by integrating Celonis Action Flows, ML Workbench, and Simulation Models, enabling proactive decision-making and “what-if” analysis with Over 10+ Prediction models
• Pioneered Agentic AI initiatives, leading multiple client POCs and implementations aligned with emerging autonomous AI patterns.
• Designed and delivered Generative AI use cases across analytics and operations, accelerating insight-to-action cycles.
• Published various enterprise-grade applications on the Celonis EMS Store, including:
  Lost Cash Discount Analytics
  Late Payment Prediction
  Duck Creek Claims Control Tower etc.
• Shaped high-value pursuits by designing analytics accelerators and representative data architectures, enabling rapid prototyping and differentiated solution narratives.
• Tools : Celonis EMS, Python, SQL, Generative AI, ML Models.

Delivered advanced analytics, AI, and optimization solutions for Fortune-scale global clients across Europe and North America.

Selected Engagement Highlights

• Global Steel Manufacturer (Germany):
  Built predictive models for production lead-time deviation and machine failure early warnings using sensor data.
  Designed inventory optimization and econometrics-based price simulators, improving planning accuracy and stock control.
• Retail Leaders (Netherlands, UK, Sweden):
  Delivered transport and load-carrier optimization under constrained data environments using heuristics + ML.
  Improved waste prediction accuracy by incorporating consumer behavior analytics.
  Designed analytics frameworks for customer segmentation, cross-sell, and personalization.
• US Retail & Consumer Goods Enterprises:
  Led RFID feasibility analytics, architecting Hadoop-based data marts for sensor data ingestion.
  Delivered sales forecasting, price elasticity, and optimization models using advanced regression, Bayesian, and ML techniques.

Tools: Python, Azure Databricks, Azure ML, PySpark, Hadoop, Hive, Tableau

fraud detection and anomaly discovery models

• Delivered predictive, rule-based, network, and cluster analysis solutions to detect misuse and leakage.
• Mentored teams and operated with high autonomy in complex analytical engagements.

Tools: Hadoop, PIG, Python, R, SQL, Hive, PolyAnalyst

• Led statistical and predictive modeling initiatives for US healthcare clients.
• Applied Bayesian methods, neural networks, time series, and optimization techniques to real-world healthcare data.

• Taught Quantitative Techniques, Research Methodology, Statistics, and Discrete Mathematics at PostGraduate Level
• Headed institutional committees and mentored postgraduate students for industry readiness.