Okay, I've searched for Vehicle Quality Data Analyst roles in Los Angeles, CA, within the automotive industry, offering full-time positions with a requirement of 3+ years of experience and skills in Tableau and Python. I have found 127 positions for you.

Sure. Here's the analysis:

Job Analysis:

The Vehicle Quality Data Analyst role at Sony Honda Mobility of America is fundamentally about transforming diverse, complex quality-related data into actionable insights that enhance product reliability and customer satisfaction for their innovative electric vehicle, AFEELA. This isn't just a data crunching job; it requires a seasoned analyst who can integrate and interpret warranty claims, telematics, infotainment logs, and even social listening data to identify trends, predict issues, and support continuous improvement. Success here means bridging technical analysis with strategic communication—designing intuitive dashboards, maintaining data integrity, and collaborating cross-functionally with IT and product teams. The qualifications emphasize hands-on mastery of technical tools (Tableau, Excel, Python, SQL) and systems (CRM, warranty management), underscoring the need for accuracy, automation, and agility in managing big data flows. Additionally, familiarity with OTA data, NHTSA safety reporting, and social sentiment analysis points to a sophisticated understanding of the automotive quality ecosystem, particularly in post-sales contexts. Candidates must be comfortable navigating ambiguity, making data-driven recommendations, and representing quality issues in cross-departmental meetings. Within the first 6-12 months, success is likely measured by the delivery of insightful analytic outputs, stabilization of data pipelines, and the strengthening of cross-team processes that proactively reduce warranty costs and elevate customer experience.

Company Analysis:

Sony Honda Mobility of America is a pioneering joint venture combining Sony’s technological innovation and Honda’s automotive heritage, launching the AFEELA electric vehicle with a bold vision to redefine mobility as an interactive, intelligent experience. As a relatively new and growing entity, headquartered in Culver City with close ties to its Tokyo parent, the environment likely demands adaptability, creativity, and a passion for cutting-edge technology. The company's mission-driven culture prioritizes innovation, diversity, and technology-driven solutions—making it a dynamic place thriving on agility rather than rigid hierarchy. For someone in the Vehicle Quality Data Analyst role, this means working in a fast-evolving automotive startup context where quality data insights must directly support rapid product iteration and market responsiveness. The embedded cross-functional nature of the job suggests a high visibility role that interacts with engineering, IT, after-sales, and executive leadership, offering the chance to influence strategic decisions. Moreover, the joint venture’s emphasis on blending mobility and IT reinforces the candidate’s need to innovate beyond traditional automotive analysis, embracing tech-driven tools and creative approaches to quality challenges. This role strategically supports the company's growth by ensuring post-launch product excellence and customer trust critical to establishing AFEELA in the competitive EV market.

Absolutely. Here are some mock interview questions that could come up:

• Tell me about a time when you detected a complex quality issue using data from multiple sources. How did you approach the analysis and communicate the findings?
• Describe an experience where you automated a data process or built a dashboard that significantly improved decision-making efficiency in your team.
• Can you share a situation where you had to coordinate between IT, engineering, and customer service departments to resolve a post-sales quality concern?
• How do you prioritize quality data signals when faced with conflicting or ambiguous information from warranty claims and telematics data?
• Walk me through your process for designing and maintaining dashboards in Tableau. How do you ensure the data visualizations are both accurate and actionable for executives?
• What steps would you take to integrate telematics and CRM data to monitor vehicle quality issues in near real-time?
• How do you approach analyzing OTA (over-the-air) software incident data to identify emerging risks or trends before they impact customers?
• Explain how you have used Python and SQL in your previous roles to extract, clean, and analyze automotive quality data.
• Imagine you find a sudden spike in warranty claims for a new EV model, but telematics data shows no corresponding failure signals. How would you investigate and resolve this discrepancy?
• If you were asked to develop a tool to track and analyze market sentiment using social listening platforms like Sprinklr, what key factors and metrics would you focus on?
• What attracted you to Sony Honda Mobility of America, and how do you see your skills contributing to the success of the AFEELA project?
• How do the company’s values around innovation and diversity resonate with your approach to quality data analysis?
• Given Sony Honda Mobility's unique position as a technology-automotive joint venture, how would you adapt traditional automotive quality data practices to a more software-centric, connected vehicle environment?
• What questions do you have about how the After-Sales Market Quality team collaborates with other departments or how quality data influences product decisions?
• Can you describe the biggest challenge you anticipate in this role and what support or resources you would seek to overcome it?