Data Scientist

LKQ Corporation; Antioch (TN); On-site; USD 110,000 - 140,000; Full time

Benefits offered by this job

Health/Dental/Vision Insurance

Paid Time Off

401k with Company Match

Life Insurance

Job summary

LKQ Corporation in Antioch, TN is seeking a Data Scientist to turn complex data into decisions that move the business, applying advanced analytics, statistical modeling, machine learning, and data science techniques to support predictive and prescriptive solutions across multiple functions.

You will collaborate with Finance, Supply Chain, Sales, Pricing, Operations, eCommerce, and Corporate Services to design models, build dashboards, and communicate insights to executives.

Qualifications

• Bachelor's degree or equivalent work experience.
• 3+ years as a professional data scientist or equivalent.
• Proven expertise in data visualization and analytics tools, especially Power BI.

Responsibilities

• Partner with business leaders across Finance, Supply Chain, Sales, Pricing, Operations, eCommerce, and Corporate Services to identify opportunities for data-driven decision making.
• Design, develop, and support scalable analytical models, machine learning solutions, and advanced data products.
• Analyze large datasets to identify trends, test hypotheses, and support enterprise initiatives.
• Build predictive, prescriptive, forecasting, optimization, and classification models to improve performance.
• Develop analytical frameworks and ML algorithms to address business challenges and support initiatives.
• Define and monitor KPIs and analytical metrics to evaluate performance.

Skills

Power BI

Excel

SQL

Data visualization

Statistical analysis

Machine learning

Programming

Cloud platforms

Cross-functional collaboration

Education

Bachelor's or Master's in Statistics/Applied Math/Physics/Engineering

Tools

Power BI

Excel

SQL

Job description

LKQ Corporation is seeking a Data Scientist to help turn complex data into decisions that move the business. In this onsite role in Antioch, TN, you will apply advanced analytics, statistical modeling, machine learning, and data science techniques to support predictive and prescriptive solutions across multiple business functions.

What you’ll do

• Partner with business leaders and subject matter experts across Finance, Supply Chain, Sales, Pricing, Operations, eCommerce, and Corporate Services to identify opportunities for data-driven decision making.
• Work with Data Engineering, Data Operations, Data Intelligence, and IT teams to design, develop, and support scalable analytical models, machine learning solutions, and advanced data products.
• Analyze large, complex, and diverse datasets to identify trends, test hypotheses, uncover business opportunities, and support enterprise initiatives.
• Build and maintain predictive, prescriptive, forecasting, optimization, and classification models to improve business performance and operational effectiveness.
• Develop analytical frameworks, statistical methodologies, and machine learning algorithms to address business challenges and support enterprise initiatives.
• Contribute to the Data Science and Advanced Analytics roadmap by identifying emerging technologies, methodologies, and opportunities to increase business value through data.
• Define, track, and monitor KPIs and analytical metrics to evaluate operational performance and measure outcomes.
• Create dashboards, reports, visualizations, and self-service analytical solutions that make complex findings clear and actionable.
• Perform ad-hoc analysis and research to support business priorities, strategic planning, and executive decision-making.
• Present findings, recommendations, and model results to technical and non-technical audiences, including management and executive leadership.
• Serve as a trusted advisor to build strong stakeholder relationships and promote data-driven decision making.

Required qualifications

• Bachelor's degree or equivalent work experience.
• 3+ years of experience as a professional data scientist or equivalent work experience (ideally in industrial goods, engineering products, distribution, or B2B sales environments).
• Proven expertise in data visualization and analytics tools, especially Power BI.
• Excellent collaboration and communication skills to build trust and influence stakeholders across functions.
• High fluency with analytics tools in a business setting, including Excel and report-building software (Power BI or SQL experience is a plus).
• Strong understanding of statistical analysis, machine learning techniques, predictive modeling, and analytical methodologies.
• Proficiency with programming languages, databases, cloud platforms, and analytical software tools.
• Ability to communicate complex analytical concepts to audiences with varying technical expertise.
• Ability to solve complex and ambiguous business problems using structured analytical approaches.
• Strong business acumen connecting analytics to measurable business outcomes.
• Ability to independently manage analytical projects from problem definition through implementation and measurement.
• Experience working in cross-functional teams supporting multiple business functions and priorities simultaneously.
• Understanding of data governance, data quality, model validation, and responsible AI practices.
• Ability to influence stakeholders and drive adoption of analytical solutions across the organization.

Tools you’ll use

• Power BI, Excel, SQL, dashboards, reports, visualizations, and self-service analytical solutions

Benefits

• Health/Dental/Vision Insurance
• Paid Time Off
• Paid Parental Leave
• Fertility Coverage
• 401k with Generous Company Match
• Company Paid Life Insurance and Long-Term Disability
• Short-Term Disability
• Employee Assistance Program
• Tuition Reimbursement
• Employee Discounts
• PNC Daily Pay Option

Work environment

• Primarily sedentary work: sit for extended periods and use a computer, keyboard, and mouse frequently.
• Occasionally lift and/or move up to 25 pounds.
• Travel may be required periodically, including overnight stays.

Preferred qualifications

• Bachelor's or Master's degree in Statistics, Applied Math, Physics, Engineering, or a related field.