What You Drive at DTNA
Applies and integrates statistical, mathematical, predictive modeling and business analysis skills to manage and manipulate complex high-volume data from a variety of sources
Develops and maintains infrastructure systems that connect internal data sets; creates new data collection frameworks for structured and unstructured data
Analyze pricing, sales, cost, and competitive data to support strategic pricing initiatives.
Build and maintain analytical models to evaluate competitive position, pricing scenarios, and performance trends
Develop, maintain and enhance dashboards and reports to track pricing KPIs and communicate insights to stakeholders
Partner with Pricing, Marketing Sales, Product, Finance, and Analytics teams on cross-functional initiatives
Support ad-hoc analyses and deep dives to answer time-sensitive business questions
Contribute to the continuous improvement of pricing tools, processes, and data quality
Knowledge You Should Bring
Bachelor's degree in Data Science, Economics, Engineering, Statistics, Business, Computer Science, Artificial Intelligence, or a related field.
Strong analytical and problem-solving skills with attention to detail.
Proficiency in Python and SQL for data analysis, statistical modeling, and machine learning development.
Experience applying predictive analytics, machine learning, optimization techniques, or advanced statistical methods to solve business problems.
Experience handling large datasets; familiarity with visualization tools (e.g., Tableau, Power BI) is preferred.
Experience with Python data science libraries such as Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch, or similar technologies is preferred.
Strong communication skills and ability to work collaboratively across teams.
Eagerness to learn, take feedback, and grow in a fast-paced environment.
Contribute to the continuous improvement of pricing tools, processes, and data quality.
Exceptional Candidates Might Have
Experience with Generative AI, Large Language Models (LLMs), prompt engineering, or AI-assisted analytics solutions.
Experience developing and deploying machine learning models in Azure, AWS, or Google Cloud environments.
Experience with advanced analytics techniques such as forecasting, optimization, price elasticity modeling, recommendation systems, or causal inference.
Master's degree in Data Science, Artificial Intelligence, Statistics, Operations Research, Computer Science, or a related quantitative field.
The ideal candidate is a highly motivated early-career analyst who enjoys working with data and solving business problems. They are collaborative, intellectually curious, and excited to build a foundation in pricing strategy within a leading OEM organization.
#LI-TN1 #LI-Hybrid
Position offers a starting salary range of $86,000 - $110,000 USD
Pay offered dependent on knowledge, skills, and experience
Benefits include annual bonus program; 401k company contribution with company match up to 6% as well as non-elective company contribution of 3 - 7% depending on age; starting at 4 weeks paid vacation; 13+ calendar holidays; 8 weeks paid parental leave; employee assistance program; comprehensive healthcare plans and wellness programs; onsite fitness (at some locations); tuition assistance and volunteer paid time off; short-term and long-term disability plans.

