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Data Analytics Systems Specialist Material Logist
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Stellantis
Lake Angelus, MI (In Person)
Full-Time
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Job Description
The Data Analytics Specialist candidate blends technical expertise with strategic vision and can translate complex data into actionable intelligence for senior leaders.
Lead data mining and analytics efforts to identify trends, uncover opportunities, and answer critical business questions across all MLM KPIs.
Design and implement robust data architecture, governance, and quality frameworks to ensure accuracy, consistency, and reliability of financial and operational data.
Leverage AI and machine learning (ML) to build predictive data models, enabling proactive decision-making on financial performance, forecasting, and overall MLM strategies.
Collaborate closely with stakeholders across MLM, Production, Finance, Audit and IT to understand data needs and translate them into scalable analytical solutions.
Partner with Data Engineering teams to optimize data pipelines, integrations, and infrastructure for Visualizations and advanced analytics.
Build and maintain interactive dashboards and self-service analytics tools that support leadership in strategic planning and performance monitoring.
Lead data mining and analytics efforts to identify trends, uncover opportunities, and answer critical business questions across all MLM KPIs.
Design and implement robust data architecture, governance, and quality frameworks to ensure accuracy, consistency, and reliability of financial and operational data.
Leverage AI and machine learning (ML) to build predictive data models, enabling proactive decision-making on financial performance, forecasting, and overall MLM strategies.
Collaborate closely with stakeholders across MLM, Production, Finance, Audit and IT to understand data needs and translate them into scalable analytical solutions.
Partner with Data Engineering teams to optimize data pipelines, integrations, and infrastructure for Visualizations and advanced analytics.
Build and maintain interactive dashboards and self-service analytics tools that support leadership in strategic planning and performance monitoring.
At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future. Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled.
Lead data mining and analytics efforts to identify trends, uncover opportunities, and answer critical business questions across all MLM KPIs.
Design and implement robust data architecture, governance, and quality frameworks to ensure accuracy, consistency, and reliability of financial and operational data.
Leverage AI and machine learning (ML) to build predictive data models, enabling proactive decision-making on financial performance, forecasting, and overall MLM strategies.
Collaborate closely with stakeholders across MLM, Production, Finance, Audit and IT to understand data needs and translate them into scalable analytical solutions.
Partner with Data Engineering teams to optimize data pipelines, integrations, and infrastructure for Visualizations and advanced analytics.
Build and maintain interactive dashboards and self-service analytics tools that support leadership in strategic planning and performance monitoring.
Basic Qualifications:
Bachelor's Degree in Analytics, Finance, Statistics, Logistics, Business or a related fieldMinimum 2 years of experience in data mining, modeling and visualization (Excel, PowerBI, Power App, Power Automate, Access, Snowflake)Excellent oral and written communication skills including working knowledge of Microsoft Office and/or Google SuiteAbility to work any shift and overtime as requiredPreferred Qualifications:
Master's Degree in Analytics, Finance, Statistics, Logistics, Business or a related fieldExperience implementing AI/ML models for predictive forecasting, anomaly detection or automated insights generationKnowledge of SQL, Python, R or other data querying / scripting languages / machine learning frameworksKnowledge of cloud-based data platforms (Snowflake, Azure, AWS, GCP)Demonstrated success in building trend analysis tools and ensure ROI justificationExperience Working in a Unionized EnvironmentStellantis Industrial Systems Logistics Pillar knowledgeThe Data Analytics Specialist candidate blends technical expertise with strategic vision and can translate complex data into actionable intelligence for senior leaders.Lead data mining and analytics efforts to identify trends, uncover opportunities, and answer critical business questions across all MLM KPIs.
Design and implement robust data architecture, governance, and quality frameworks to ensure accuracy, consistency, and reliability of financial and operational data.
Leverage AI and machine learning (ML) to build predictive data models, enabling proactive decision-making on financial performance, forecasting, and overall MLM strategies.
Collaborate closely with stakeholders across MLM, Production, Finance, Audit and IT to understand data needs and translate them into scalable analytical solutions.
Partner with Data Engineering teams to optimize data pipelines, integrations, and infrastructure for Visualizations and advanced analytics.
Build and maintain interactive dashboards and self-service analytics tools that support leadership in strategic planning and performance monitoring.
At Stellantis, we assess candidates based on qualifications, merit, and business needs. We welcome applications from all people without regard to sex, age, ethnicity, nationality, religion, sexual orientation, disability, or any characteristic protected by law. We believe that diverse teams reflect our identity as a global company, enabling us to better address the evolving needs of our customers and care for our future. Equal Opportunity Employer Minorities/Women/Protected Veterans/Disabled.