Data Scientist: Enterprise Analytics & Strategic Impact

Lkq-Corporation; Antioch (TN); On-site; USD 90,000 - 130,000; Full time

Benefits offered by this job

Health/Dental/Vision Insurance

Paid Time Off

Paid Parental Leave

401k with Company Match

Life Insurance

Short-Term Disability

Tuition Reimbursement

Employee Discounts

Job summary

LKQ Corporation seeks a Data Scientist to apply advanced analytics, statistical modeling, and machine learning to drive data-informed decisions across Finance, Supply Chain, Sales, Pricing, and Operations.

The role partners with data engineers and IT leadership to build scalable models and dashboards, delivering insights that improve efficiency, customer experience, and financial performance enterprise-wide.

Qualifications

• Bachelor's degree in a quantitative field; Master’s preferred.
• 3+ years of professional data science experience.
• Strong skills in statistical analysis and modeling.
• Ability to communicate complex analytics to non-technical stakeholders.

Responsibilities

• Partner with business leaders across Finance, Supply Chain, Sales, Pricing, Operations, and eCommerce to identify data-driven opportunities.
• Collaborate with Data Engineering and IT to design, develop, and support scalable analytical models and ML solutions.
• Analyze large datasets to identify trends, test hypotheses, and support strategic initiatives.
• Develop predictive, prescriptive, forecasting, and optimization models to improve performance.
• Create dashboards, reports, and self-service analytics to communicate findings.

Skills

Statistical analysis

Machine learning

Data visualization

Python

Power BI

SQL

Excel

Communication

Education

Bachelor's degree in a quantitative field

Master's degree preferred

Tools

Python

R

SQL

Power BI

Job description

LKQ Corporation seeks a Data Scientist to apply advanced analytics, statistical modeling, and machine learning to drive data-informed decisions across Finance, Supply Chain, Sales, Pricing, and Operations.

The role partners with data engineers and IT leadership to build scalable models and dashboards, delivering insights that improve efficiency, customer experience, and financial performance enterprise-wide.