Data Scientist
PACCAR Parts
Location
🇺🇸 Renton, United States
Type
full_time
Salary
Undisclosed
Posted
1w ago
Job Description
Requisition Summary As a Data Scientist you’ll support the growth of PACCAR Parts by using industry-leading tools such as AWS, Snowflake, and Python to build, deploy, and manage AI and machine learning models and workflows. Additionally, you’ll support others by being a technical lead in order to support the development of other Associate Data Scientists. This position is a part of the Advanced Analytics team, a collaborative group who create Analytics solutions with AI and Machine Learning for any department in the PACCAR Parts Division. As a member of this team, you’ll work on highly visible and impactful projects that support the strategic initiatives set by PACCAR Parts Leadership. Each team member will get the opportunity to present their work to Senior Executives, helping to shape PPD’s current business and long-term Analytics strategy. Job Functions /
Responsibilities
- Serve as an expert on PACCAR Parts data sources
- Build & deploy advanced analytics solutions using AI, machine learning, statistics, or other mathematical concepts for business departments.
- Develop advanced analytics models; including creating, validating, analyzing and explaining the data used for model development
- Support production algorithms that use more advanced concepts such as reinforcement learning.
- Lead conversations with stakeholders to gather project
requirements
and other relevant information to support the development of assigned projects. • Regularly present analysis, updates, and project solutions to leadership and key stakeholders • Support the development of other data analysts by leading technical trainings on SQL, Python, Tableau, and/or data analysis • Candidate must demonstrate strong analytical skills, excellent general business acumen, with the ability to concisely and clearly communicate complex topics. • Able to work with stakeholders from any department to develop new analytics solutions, identify necessary data, and support analytics best practices.