Data Analytics Supervisor

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.

Exempt

Kia North America Ownership Experience - Product Quality team aims to represent the voice of the North American customer in identification of vehicle quality concerns and development of countermeasures for Kia America’s vast dealership network. This team collaborates with engineering groups in North America and Korea to turn this goal into reality.

The Data Analytics Supervisor will utilize data to develop models to support Product Quality Engineers in improving vehicle quality by developing models to determine potential emerging quality concerns. This position will also support the improvement of existing systems and analysis methods, as well as collaborate with IT affiliates and outside vendors as necessary to maintain and enhance Product Quality’s data systems.

This individual should have a strong programming background, and a critical thought process to troubleshoot issues and find solutions. This individual should be a self-starter, able to work independently with minimal direction and oversight, and deliver and communicate solutions which meet Product Quality’s business needs.

1st Priority - 40%

• Design and maintain processes and tools for Product Quality engineers to access, analyze, and investigate potential emerging quality concerns.
• Build prediction and classification models.

2nd Priority - 30%

• Build visualizations and dashboards to support Product Quality team operations.

3rd Priority - 20%

• Manage and oversee Product Quality team’s IT projects through collaborations with IT affiliates and/or outside vendors.

4th Priority - 10%

• Provide ad-hoc data analysis solutions to internal and external stakeholders to assist in monitoring field data, conducting investigations, and making informed business decisions.

• Bachelor’s degree or equivalent experience in Analytics, Data Science, Engineering, Statistics, Computer Science, or another quantitative field required.

Overall

Experience:

• Minimum of 5 years of data analytics experience required, specifically modeling/reliability analysis.
• Prior projects related to reliability and/or quality preferred.

Directly Related

Experience:

• Experience with SAS, SQL, Python, R, or another programming language with focus on data analysis.
• Experience developing predictive models on time-series data is strongly desired.
• Experience supporting engineering, quality, or statistical analysis (Maximum Likelihood Estimation, Bayesian methods, Monte Carlo analysis, Weibull distribution, etc.)
• Experience working with and creating relational databases, and highly integrated systems.
• Experience building visualizations and dashboards for stakeholders (e.g., using SAS Visual Analytics and Power BI).
• Experience utilizing machine learning and AI is a plus.

• Experience building visualizations and dashboards (SAS Visual Analytics, Power BI, etc.)
• Proficient knowledge of PC and software (Word, Excel, PowerPoint, Outlook, etc.)
• Proven ability to execute projects with self-starting attitude, responsibility, and accountability.
• Strong programming background. Proficiency with relational databases and integrated systems.
• Strong technical writing capabilities and…