WMS Business Analyst/Data Scientist (Mopar Parts & Services - North America)

Key Responsibilities:

Data Engineering & Pipeline Development:

• Design, implement, and maintain robust data pipelines (ETL/ELT) to collect, process, and transform large-scale structured and unstructured datasets from diverse automotive sources.
• Ensure data quality, integrity, and accessibility by developing automated validation and monitoring tools.
• Optimize data workflows for performance, scalability, and reliability, supporting both batch and real-time analytics needs.
• Collaborate with IT and analytics teams to integrate data from business systems into centralized data products.
• Build, train, and deploy predictive models and machine learning algorithms for applications such as performance forecasting, anomaly detection, and customer segmentation.
• Apply best practices in data visualization to ensure clarity, accuracy, and accessibility of insights, including interactive dashboards, automated reporting, and mobile-friendly solutions.

Collaboration & Stakeholder Engagement:

• Serve as a technical liaison between HQ analytics and business teams, translating business needs into scalable data solutions.
• Educate and mentor team members on data best practices, analytics tools, and emerging technologies.

Basic Qualifications:

• Bachelor's degree in Computer Science, Data Engineering, Data Science, Information Systems, or a related field, or equivalent work experience
• Minimum 1 year experience in data engineering, analytics, or data science (automotive industry experience preferred)
• Proficiency in programming languages such as Python and SQL
• Hands-on experience with ETL/ELT tools, data modeling, and cloud platforms (Snowflake, etc.)
• Strong analytical thinking, problem-solving skills, and attention to detail
• Excellent communication and presentation abilities, with a proven ability to explain complex technical concepts to diverse audiences
• Ability to manage multiple priorities and deliver results in a fast-paced environment

Preferred Qualifications:

• Master Degree in Computer Science, Data Engineering, Data Science, Information Systems, or a related field
• Demonstrated experience designing and deploying business dashboards and data visualizations for large-scale automotive or after-sales operations
• Advanced proficiency with business intelligence tools (e.g., Power BI, Tableau, Qlik) and experience integrating visualizations with cloud data platforms (e.g., Snowflake)
• Familiarity with Mopar systems and performance metrics
• Knowledge of machine learning, deep learning, and advanced analytics techniques
• Certifications in cloud data engineering or analytics platforms

Key Responsibilities:

Data Engineering & Pipeline Development:

• Design, implement, and maintain robust data pipelines (ETL/ELT) to collect, process, and transform large-scale structured and unstructured datasets from diverse automotive sources.
• Ensure data quality, integrity, and accessibility by developing automated validation and monitoring tools.
• Optimize data workflows for performance, scalability, and reliability, supporting both batch and real-time analytics needs.
• Collaborate with IT and analytics teams to integrate data from business systems into centralized data products.
• Build, train, and deploy predictive models and machine learning algorithms for applications such as performance forecasting, anomaly detection, and customer segmentation.
• Apply best practices in data visualization to ensure clarity, accuracy, and accessibility of insights, including interactive dashboards, automated reporting, and mobile-friendly solutions.

Collaboration & Stakeholder Engagement:

• Serve as a technical liaison between HQ analytics and business teams, translating business needs into scalable data solutions.
• Educate and mentor team members on data best practices, analytics tools, and emerging technologies.