Data Scientist

Kawasaki Motors Corp., U.S.A.•Lake Forest, CA

9d•$110,000 - $115,000•Onsite

About The Position

Kawasaki Motors Retail Finance is seeking a Data Scientist to manage and analyze complex data for retail finance operations. The role uses data-driven insights to optimize performance, enhance decision-making, and support business strategies, particularly in the retail finance domain. This position reports to the Senior Group Manager, Data Science. The Data Scientist develops and maintains predictive models for credit risk assessment, loan performance forecasting, customer segmentation, and pricing strategies; manages and analyzes large structured and unstructured datasets; performs exploratory analysis to identify trends and opportunities in the retail finance powersports market; and collaborates across business teams to translate objectives into data science solutions. The role also develops dashboards and reporting tools, maintains data quality and governance, improves processes and pipelines, communicates findings and recommendations, keeps current with data science and fintech developments, and ensures compliance with applicable regulations and company policies. Other duties may be assigned to support the analytics and retail finance teams.

Requirements

Bachelor’s degree in data science, computer science, statistics, or a related field.
At least 3 years of experience in data science or advanced analytics, including direct experience in retail finance or financial services.
Strong proficiency in Python, R, and SQL for data manipulation and model development.
Hands-on experience with machine learning frameworks and algorithms, such as scikit-learn, XGBoost, and TensorFlow.
Expertise in statistical modeling, forecasting, and financial analytics techniques.
Proficiency with data visualization tools such as Power BI, Tableau, or similar platforms.
Familiarity with cloud platforms and modern data pipeline tools, such as AWS, Azure, Snowflake, and Airflow.
Strong problem-solving and critical-thinking skills and attention to detail.
Strong verbal and written communication skills, including the ability to present complex data insights to technical and non-technical stakeholders.
Ability to work on-site at the Foothill Ranch, California office and work collaboratively as part of a team.

Nice To Haves

Master’s or advanced degree.
Demonstrated success in fast-paced startup or high-growth environments, especially as a founder, co-founder, or early-stage team member.
Direct experience or strong familiarity with powersports finance, including motorcycles, ATVs, UTVs, PWCs, retail installment contracts, dealer networks, and consumer behavior.
Deep understanding of fintech trends and applications affecting consumer lending, digital finance platforms, alternative credit models, and financial-services automation.
Expertise writing optimized complex SQL queries and working with large-scale relational databases; experience in data wrangling, ETL, and performance tuning.
Hands-on experience with cloud platforms and tools including AWS, Azure, Snowflake, Airflow, S3, Redshift, Glue, EMR, Azure Synapse, and Data Factory.
Ability to connect technical analysis with business strategy and deliver insights supporting revenue growth, risk mitigation, and operational efficiency.
Business acumen at the intersection of data science, finance, and product strategy, including understanding consumer-lending and asset-backed-finance drivers and KPIs.
Self-starter mentality and interest in building, optimizing, and scaling data-driven systems and solutions.

Responsibilities

Design, build, and maintain predictive models for credit risk assessment, loan performance forecasting, customer segmentation, and pricing strategies.
Manage, clean, and analyze large-scale structured and unstructured datasets to generate actionable insights.
Perform exploratory data analysis to uncover trends, patterns, and business opportunities in the retail finance powersports market.
Partner with cross-functional teams to understand business objectives and translate them into data science solutions with measurable impact.
Develop, maintain, and optimize interactive dashboards and reporting tools to track KPIs, monitor portfolio performance, and support data storytelling.
Ensure the accuracy, consistency, and security of financial data in accordance with regulatory standards and internal governance policies.
Identify and implement automation, workflow improvements, and advanced analytics use cases to streamline operations and improve decision-making.
Coordinate with IT and engineering teams to design scalable data pipelines and improve integrations across internal systems and third-party platforms.
Communicate clear, concise, data-backed insights and recommendations to stakeholders at all levels.
Stay current with emerging data science and fintech technologies, tools, and methodologies and apply innovations to improve business outcomes.
Ensure data activities, models, and reporting processes comply with applicable financial regulations and company policies.
Perform other duties as assigned to support the analytics and retail finance teams.