Data Scientist

LKQ•Nashville, TN

5d•Onsite

About The Position

Responsible for leveraging advanced analytics, statistical modeling, machine learning, and data science techniques to drive data-informed decision-making across multiple business functions. Partners with business stakeholders, data engineers, analytics teams, and IT leadership to identify opportunities, develop predictive and prescriptive solutions, and deliver actionable insights that improve operational efficiency, customer experience, financial performance, and strategic outcomes across the enterprise. Collaborates with cross-functional teams to transform complex data into scalable analytical solutions, enabling business functions to make more effective and consistent decisions through data-driven insights.

Requirements

Bachelor's Degree or equivalent work experience.
3+ years of experience as a professional data scientist or equivalent work experience.
Demonstrated expertise in data visualization and analytics tools, especially Power BI.
Excellent collaboration and communication skills, with the ability to build trust and influence stakeholders across functions.
High fluency using analytics tools in a business setting, including Excel and report-building software (experience with Power BI or SQL a plus).

Nice To Haves

Ideally, within industrial goods, engineering products, distribution, or B2B sales environments.
Bachelor's or Master's degree in Statistics, Applied Math, Physics, Engineering, or a related field.
Strong understanding of statistical analysis, machine learning techniques, predictive modeling, and analytical methodologies.
Demonstrated 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 with the ability to connect analytical findings 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.

Responsibilities

Partner with business leaders and subject matter experts across multiple functions including Finance, Supply Chain, Sales, Pricing, Operations, eCommerce, and Corporate Services to identify opportunities for data-driven decision making.
Collaborate 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 strategic initiatives across the enterprise.
Develop and maintain predictive, prescriptive, forecasting, optimization, and classification models that improve business performance and operational effectiveness.
Design and implement 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 key performance indicators (KPIs) and analytical metrics to evaluate operational performance, measure outcomes, and support continuous improvement initiatives.
Create dashboards, reports, visualizations, and self-service analytical solutions that communicate complex findings in a clear and actionable manner.
Conduct ad-hoc analysis and research to support business priorities, strategic planning, and executive decision-making.
Present analytical findings, recommendations, and model results to technical and non-technical audiences, including management and executive leadership.
Build strong relationships with business and technology stakeholders by serving as a trusted advisor and advocate for data-driven decision making.
Assumes other duties as assigned.