Data Analytics Specialist - Employee Relations

Stellantis is seeking a Data Analytics Specialist to develop analytical tools and insights that improve workforce attendance, support operational performance, and strengthen Employee Relations decision-making.

The primary focus of the role is attendance and absenteeism analytics. The successful candidate will partner with Employee Relations, Manufacturing, IT, and other functions to consolidate data, identify trends and root causes, and translate findings into actionable recommendations.

Primary Responsibilities

• Analyze attendance, absenteeism, operational performance, employee engagement, and related Employee Relations issues.
• Collect, cleanse, integrate, validate, and analyze data from multiple sources.
• Develop and improve recurring absenteeism reports, dashboards, scorecards, and key performance indicators.
• Identify trends, root causes, emerging risks, and predictive indicators affecting workforce availability and business performance.
• Translate analytical findings into clear recommendations for Employee Relations and Manufacturing leadership.
• Apply statistical analysis, machine learning, artificial intelligence, and data visualization to support business decisions.
• Build and maintain repeatable data pipelines, datasets, queries, and analytical tools.
• Use advanced Microsoft Excel, Access, Power Query, SQL, and related technologies to prepare data, automate reporting, and improve analytical efficiency.
• Communicate findings through concise visualizations, presentations, and executive summaries.

Basic Qualifications

• Bachelor's degree, or anticipated completion of a bachelor's degree, in Computer Science, Data Science, Statistics, Applied Mathematics, Operations Research, Engineering, or a related quantitative field
• A minimum of 3 years of experience supporting data science, advanced analytics, business analytics, or statistical modeling projects
• Advanced proficiency in Microsoft Excel, Access, Power Query, and SQL
• Experience integrating, cleansing, validating, and analyzing data from multiple sources
• Working knowledge of statistical analysis, machine learning, artificial intelligence, data visualization, and dashboard development
• Ability to translate complex data into practical business recommendations
• Strong communication, problem-solving, and cross-functional collaboration skills
• Experience with benchmarking and performance comparisons
• Strong presentation and data-storytelling skills

Preferred Qualifications

• Master's degree, or equivalent experience, in a quantitative field
• Five or more years of experience delivering data science or advanced analytics projects
• Experience in attendance, workforce, manufacturing, operational, employee, or customer analytics
• Proficiency in Python or R and experience with predictive modeling or data mining
• Experience with business intelligence and automation tools such as Power BI, QlikView, Cognos, VBA, or Power Automate
• Knowledge of manufacturing operations, finance, labor economics, behavioral economics, or project and change management

Stellantis is seeking a Data Analytics Specialist to develop analytical tools and insights that improve workforce attendance, support operational performance, and strengthen Employee Relations decision-making.

The primary focus of the role is attendance and absenteeism analytics. The successful candidate will partner with Employee Relations, Manufacturing, IT, and other functions to consolidate data, identify trends and root causes, and translate findings into actionable recommendations.

Primary Responsibilities

• Analyze attendance, absenteeism, operational performance, employee engagement, and related Employee Relations issues.
• Collect, cleanse, integrate, validate, and analyze data from multiple sources.
• Develop and improve recurring absenteeism reports, dashboards, scorecards, and key performance indicators.
• Identify trends, root causes, emerging risks, and predictive indicators affecting workforce availability and business performance.
• Translate analytical findings into clear recommendations for Employee Relations and Manufacturing leadership.
• Apply statistical analysis, machine learning, artificial intelligence, and data visualization to support business decisions.
• Build and maintain repeatable data pipelines, datasets, queries, and analytical tools.
• Use advanced Microsoft Excel, Access, Power Query, SQL, and related technologies to prepare data, automate reporting, and improve analytical efficiency.
• Communicate findings through concise visualizations, presentations, and executive summaries.