Kieso Jan

Background

About Kieso Jan

Over 2 decades of working experience with integrated & accumulated knowledge in fields of:(a) Human Resource: People Analytics of Employee Lifecycle / HR Digital Transformation (b) Corporate Business Process Digitalization, BI Platform Establishment, and Advanced Data-Driven Analytics / Data Science.(c) Automotive Finance and Controlling / Risk Management Methodology.(d) Software Engineering. Good at providing digital solutions via strategic view with solid communication skills for solving business problems & performance improvement in complex system & process environments by acting in multiple roles simultaneously, including Project Manager, Task Initiator, and Digital Architect. I enjoy working in a challenging environment and taking responsibility for implementing ideas to create efficient, innovative A. Business Domain Knowledge in Human Resource & Automotive Financial Services (1) Human Resource Digital Solution for Talent Acquisition, Employee Lifecycle Mgt, Performance & Development mgt (2)Automotive Financial Services Controlling KPI Reporting, Monitoring & Planning Methodology including Sales Controlling, Corporate Controlling, Cost Controlling (3) Automotive Financial Services Risk Management / Monitoring Methodology & Process: Portfolio Risk Mgt. & Auto Finance Risk Instrument (Retail Score Card, Dealer Rating)(4) ABS (Asset-Backed Securitization) Business Process B. Enterprise Digital Strategy / Solution, and BI Platform Establishment A. Process Data Digital Eco-System Design to Realization by RPA (Robotic Process Automation) & e-flow Solution:(1) AS-IS Business Process Scanning & Problem finding and setup Target process improving method with process stakeholder (2) Covert AS-IS Process requirement to TO-BE digital process by digital approach to fulfil FTE saving, increasing efficiency & generate qualified/standard process data (3) Establish the Process Literation cycle by performance monitoring and feedback mechanism (process data generation & process data storage design. C. Familiar with Data-Driven Analysis & Data Science Method Design & Implementation:(1) Business Process Performance Measurement / Improvement by Statistical Methodology (via R and Python).(2) Data Science Life Cycle (including Business Demand Clarification, Data Collection & Cleaning, Data Exploration, Modeling / Forecasting, ML, etc.)