Emerging Field Data Engineer/Specialist

Kia USA•Irvine, CA

65d

About The Position

At Kia, we're creating award-winning products and redefining what value means in the automotive industry. It takes a special group of individuals to do what we do, and we do it together. Our culture is fast-paced, collaborative, and innovative. Our people thrive on thinking differently and challenging the status quo. We are creating something special here, a culture of learning and opportunity, where you can help Kia achieve big things and most importantly, feel passionate and connected to your work every day. Kia provides team members with competitive benefits including premium paid medical, dental and vision coverage for you and your dependents, 401(k) plan matching of 100% up to 6% of the salary deferral, and paid time off. Kia also offers company lease and purchase programs, company-wide holiday shutdown, paid volunteer hours, and premium lifestyle amenities at our corporate campus in Irvine, California. General Summary The purpose of this position is to support the Emerging Field Data Manager and Emerging Field Data Team (EFD) by identifying at an early stage in a model's life cycle, any emerging potential safety and noncompliance issues through Kia's Safety Data Analytics Infrastructure (SDAI) system and other supporting applications. This includes review of Kia America (KUS) warranty, Techline, Customer Care, field reports, and quality information reports, as well as NHTSA Vehicle Owner Questionnaires (VOQs) and other data sources, as applicable. This position will be responsible for performing detailed screening of potential safety issue alerts and escalating relevant alerts for further data analysis and/or investigation. This involves review of data across data sources to identify frequency, severity, and detectability of alerted issues. The position will also provide verbal reports to management, other Data Evaluation Team (DET) members, and Forensic Engineering & Investigations team members, and support data analysis efforts in the investigation of potential safety and noncompliance issues.

Requirements

3-7 years of experience in technical positions such as safety analysis, product quality, technical customer assistance, or in a product engineering environment.
Written and oral technical communications experience.
Automotive, aerospace, commercial vehicle, or similar technical work experience required.
Working knowledge of statistical analysis concepts and software.
Schedule(s) may vary due to needs of the business including but not limited to working outside of normal business hours, travel, weekends and/or holidays.
Must have a valid driver's license. Position requires driving Kia and competitor vehicles to evaluate vehicles.
Perform other duties as assigned.
Excellent written and oral communication skills.
Excellent analytical skills and attention to detail.
Excellent teamwork skills.
Intermediate knowledge of automotive systems and components.
Knowledge of PC software such as Microsoft Excel and PowerPoint.
Knowledge of statistics.
Knowledge of SAS programing language and Structured Query Language (SQL).
Knowledge of SAS Visual Analytics.
Engineer: BS degree in Engineering or Automotive Technology or equivalent work experience required.
Specialist: Bachelors degree in technical field or equivalent work experience.

Responsibilities

Perform detailed screening of potential safety issue alerts and escalate relevant alerts for further data analysis and/or investigation. Work from SDAI dashboards to identify frequency, severity, and detectability of alerted issues.
Evaluate escalated alerts for any potential trends and communicate findings to Emerging Field Data Manager. Collaborate with the Data Evaluation Team or Forensic Engineering and Investigation Team to support further data analysis.
Develop sophisticated monitoring criteria to ensure that any developments on closed cases are tracked in a timely manner.
Assist in the continuous improvement and development of Safety Data Analytics Infrastructure (SDAI) by creating training data for improving machine learning model accuracy and communicating opportunities to improve efficiency to Emerging Field Data Manager.