Data Analytics Manager

Kia Corporation•Tustin, CA

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.Status Exempt General SummaryThe Data Analytics Manager is responsible for defining, leading, and executing the end-to-end data strategy that enables the Kia North America Product Quality team to identify, prioritize, and address potential emerging vehicle quality concerns. The role manages the frameworks, systems, and analytical methodologies used to integrate traditional and non-traditional data sources, develop advanced statistical and AI models, and translate complex market indicators into actionable quality insights. The Manager will work closely with their peers to lead Product Quality data analytics. This includes overseeing model development, data source management, AI implementation and validation, system management and enhancements, and alignment with engineering, IT, and external third-party partners. The role will utilize a strong programming background and critical thinking to troubleshoot issues, find solutions, and gain consensus. Essential Duties and ResponsibilitiesESSENTIAL DUTIES Priority One – 40% Define and manage Product Quality’s data and analytics strategy, including data sources, modeling frameworks, AI integration, and issue-ranking methodologies. Priority Two – 30% Lead development of prediction and classification models. Build visualizations and dashboards to support Product Quality team operations. Priority Three – 20% Manage analytics platforms, dashboards, and reporting strategies to support operational decision making. Priority Four – 10% Oversee Product Quality team’s IT projects through collaborations with IT affiliates and/or outside vendors. This list of essential responsibilities and duties is not exhaustive and may be supplemented and changed as necessary by management. DAY-TO-DAY DUTIES Design and maintain product quality processes and tools: Analyze large amounts of data to discover trends of patterns. This can include, but is not limited to, data from Kia’s dealership network obtained through warranty and vehicle diagnostics. Build prediction and classification models. Test and continuously improve the accuracy of models. Create methodology to identify and rank potential quality issues to support Service Engineering team. Investigate new technologies to investigate and quantify non-traditional product quality feedback. Build visualizations and dashboards: Work within Product Quality Data Analytics team to develop visualizations and dashboards to assist Service Engineering team in investigation of potential quality concerns. Manage Product Quality IT projects: Collaborate with IT affiliates and/or outside vendors to develop, maintain, and improve product quality systems. Ensure that Product Quality systems are aligned with other corporate efforts. Support Data Analysis: Provide analysis in monitoring field data, conducting investigations, and making informed business decisions.

Requirements

Bachelor’s degree or equivalent experience in Analytics, Data Science, Engineering, Statistics, Computer Science, or another quantitative field required.
Minimum of 7 years of data analytics experience required specifically modeling/reliability analysis.
Demonstrated experience leading analytics strategy, projects, or teams required.
Prior projects related to reliability and/or quality required.
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).
Strong technical writing capabilities and oral communication skills
Experience querying databases using statistical computer languages (SAS, Python, R, SQL, etc.)
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.

Nice To Haves

Masters’s degree preferred.
Experience with HTML and JavaScript is a plus.
Experience utilizing machine learning and AI is a plus.

Responsibilities

Define and manage Product Quality’s data and analytics strategy, including data sources, modeling frameworks, AI integration, and issue-ranking methodologies.
Lead development of prediction and classification models. Build visualizations and dashboards to support Product Quality team operations.
Manage analytics platforms, dashboards, and reporting strategies to support operational decision making.
Oversee Product Quality team’s IT projects through collaborations with IT affiliates and/or outside vendors.
Design and maintain product quality processes and tools
Build visualizations and dashboards
Manage Product Quality IT projects
Support Data Analysis