Data Management

RONG JING

• **** Mystic Forest Ct, Canton, MI ***87 • Cell: 313-***-**** • Email: ac272o@r.postjobfree.com

SUMMARY

IT Business Analyst with 3 plus years of experience in the automotive industry performing ETL requests, discovering insights in the data, building visualizations for decision making, collaborating cross-functionally and regionally with subject matter experts and business partners, and developing best practices. Proficient with SQL, Tableau, Qlikview, Alteryx, SAS, R, Python, Excel and PowerPoint. Strong interpersonal skills, business acumen, ability to think creatively and critically, thrive in a fast-paced, dynamic and often ambiguous work environment.

EDUCATION

M.S. in Industrial System Engineering University of Michigan, Dearborn, MI 08/2014

Rackham Graduate School, GPA: 4.0/4.0

B.S. in Industrial Engineering Xi’an Jiaotong University, China 07/2012

School of Management (AACSB Certification), Overall GPA: 3.7/4.0

PROFESSIONAL EXPERIENCE

Ford Motor Company, Business Analyst IT, Dearborn, MI 06/2014~

Complexity Reduction Enterprise Tech Refresh Project

Delivered analytical solutions for Enterprise Tech Refresh program to eliminate retired and terminated technologies, improved readiness for data center implementation, identified pain points (bottleneck) in the current process and developed future state process metrics

Performed data prepping and blending of multiple (10 plus) data sources in Alteryx to access enterprise application and technology health and defined business rules to accommodate data discrepancies

Built and maintained visualizations using Tableau and Qlikview to conduct ad-hoc data analysis, provide agile responses, and facilitate decision making process

Designed data-driven analytical approach to prioritize tech refresh activities and optimize the investment

Effectively engaged with business partners and facilitated meetings on a regular basis

Business Value Framework to prioritize PD and IT investments

Developed a sophisticated-simple, data-driven and business-friendly approach for prioritizing and ranking potential investments that includes defining investment strategy, prioritization process, and execution timing

Created structured workbook for data collection, consolidated data and performed data analysis across 50-70 projects to evaluate cost vs strategic benefits and hard savings

Constantly communicated with organizational reps and business relationship managers (BRM) to get common understanding and provided training to project teams for data entering

Presented investment ranking and benefits to the leadership

Knowledge Management Project

Led a team of 3 that implemented a proof of concept for capturing IT knowledge of the business and established qualitative models for identifying agility and efficiency opportunities in IT

Created project charter, milestones, timing, RASIC and governance structure

Conducted interviews and document analysis to model IT process and measure efficiency

Facilitated governance meetings, presented deliverables and identified IT opportunities for continuous improvements

University of Michigan, Research Assistant, Dearborn, MI 07/2012~05/2014

University Project: Business Intelligence for Customer Relationship Management

Ran queries from raw data for ad-hoc analysis with SQL based tools such as Microsoft Access and SAS Enterprise Guide to extract and cleanse large data sets

Developed a customer behavioral segmentation model using Principle Component Analysis and K-means Cluster Analysis to segment customer groupings for campaign management

Introduced a new approach to define Customer Lifetime Value based on purchase likelihood prediction results

Improved customer retention rate by utilizing predictive modeling methods to target potential escalation customers for the marketing department

Ford Project: Lithium-ion Battery State-of-Charge Estimation under Uncertainties

Realized 10% accuracy improvement of SOC estimation with considering of parameter and model uncertainties

Planned, scheduled, and performed testing procedures of lithium-ion batteries in the battery cycler using DOE techniques for data acquisition purpose

Precisely identified model parameters for a nonlinear battery model with Matlab Optimization Toolbox, and applied statistics and data-driven tools to quantify3 model uncertainties in Matlab

Developed and delivered the state-of-art simulation packages of proposed framework including battery model, parameter uncertainty identification and model bias characterization

Presented to technical experts and academic professionals at 2013 Annual Conference of PHM Society

Ford Project: Robust and Reliability-based Design Optimization (RBDO) with Effective Model Validation

Improved overall accuracy of frontal impact performances by 25% with real vehicle crash safety data through the implementation of RBDO

Carried out an effective model validation employing cross validation method

Proposed the approach and case study findings to technical experts and academic professionals at 2013 ASME-39th Design Automation Conference

PUBLICATIONS & AWARDS

Zhimin Xi, Rong Jing, Choel Lee: Recent research on battery diagnostics, prognostics, and uncertainty management, Advances in Battery Manufacturing, Service, and Management Systems, 2016

Rong Jing, Zhimin Xi, Xiaoguang Yang, Ed Decker: SOC Estimation of Lithium-ion Batteries Considering Model and Parameter Uncertainties, International Journal of Prognostics and Health Management (IJPHM), 2014

Xi, Z., Jing, R, Wang P., Hu C.: A Copula-based sampling method for data-driven prognostics and health management, Journal of Reliability Engineering and System Safety, 2013

Honor Scholar Award (ranked top one in the program), UM-Dearborn, 2014

Best Paper Award, ASME-39th Design Automation Conference, 2013

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