Data Scientist

Responsibilities

The Data Scientist will design and maintain predictive models for credit risk and loan performance while managing large-scale datasets to generate actionable business insights. They will also collaborate cross-functionally to develop dashboards and optimize data pipelines to support strategic financial planning.

Requirements

Candidates must have at least a bachelor's degree in a quantitative field and a minimum of 3 years of experience in data science or advanced analytics. Proficiency in Python, R, SQL, and machine learning frameworks is required, along with the ability to work on-site in Foothill Ranch, CA.

Skills

• Python
• R
• SQL
• Machine learning
• Statistical modeling
• Forecasting
• Tableau
• Power BI
• Looker
• AWS
• Azure
• Snowflake
• Airflow
• Data visualization
• Credit risk assessment
• Data analysis

Benefits

• Medical insurance
• Dental insurance
• Vision insurance
• Pet insurance
• 401(k) match
• Life insurance
• Disability benefits
• Generous PTO policy
• Paid company holidays
• Employee discounts
• Onsite fitness center

About this role

Kawasaki Motors Retail Finance is seeking a highly skilled and experienced Data
Scientist to manage and analyze complex data for our retail finance operations.
This role is pivotal in leveraging data-driven insights to optimize performance,
enhance decision-making, and support business strategies. The ideal candidate
will have a strong background in data analysis, statistical modeling, and
machine learning techniques, particularly within the retail finance domain. This
position will report to the Senior Group Manager, Data Science.

Model Development & Forecasting:
Design, build, and maintain advance predictive models to support credit risk
assessment, loan performance forecasting, customer segmentation, and pricing
strategies.
Data Management & Analysis:
Manage, clean, and analyze large-scale, structured, and unstructured datasets to
generate actionable insights that inform business strategies and drive
operational efficiency.
Exploratory Data Analysis (EDA):
Perform deep-dive analysis to uncover trends, patterns, and new business
opportunities in the retail finance powersports market.
Cross-functional Collaboration:
Partners with teams across the business to understand key objectives and
translate them into data science solutions that drive value and measurable
impact.
Dashboarding & Visualization:
Develop, maintain, and optimize interactive dashboards and reporting tools
(Tableau, Power BI, Looker) to track KPI’s monitor portfolio performance, and
support data storytelling.
Data Quality & Governance:
Ensure the accuracy, consistency, and security of financial data while
maintaining compliance with regulatory standards and internal governance
policies.
Process Improvement:
Identify and implement opportunities for automation, workflow enhancements, and
advanced analytics use cases to streamline data operations and improve decision
making.
Pipeline Optimization:
Coordinate with IT and engineering teams to design robust, scalable data
pipelines and improve integration processes across internal systems and
third-party platforms.
Strategic Insight & Communication:
Deliver clear and concise insights and data backed recommendations to
stakeholders at all levels, supporting strategic initiatives and financial
planning processes.
Continuous Learning & Innovation:
Stay abreast of emerging technologies, tools, and methodologies in the data
science and fintech landscape and apply innovative technologies to enhance
business outcomes.
Regulatory & Policy Compliance:
Ensure all data activities, models and reporting processes comply with
applicable financial regulations and company policies.
Additional Responsibilities:
Perform other duties as assigned to support the growth and success of the
analytics and retail finance teams.

Qualifications:

* Bachelor’s degree in data science, Computer Science, Statistics, or a related
field required; master’s or advanced degree is preferred.
* A minimum of 3 years of experience in data science or advance analytics, with
direct experience in retail finance or financial services is required.
* Strong proficiency in Python, R, and SQL for data manipulation and model
development.
* Hands-on experience with machine learning frameworks and algorithms
(scikit-learn, XGBoost, TensorFlow).
* Expertise in statistical modeling, forecasting, and financial analytic
techniques.
* Proficient with data visualization tools such as Power BI, Tableau, or
similar platforms.
* Familiarity with cloud platforms and modern data pipeline tools (AWS, Azure,
Snowflake, Airflow).
* Excellent problem solving and critical thinking skills with sharp attention
to detail.
* Strong verbal and written communication skills, with the ability to clearly
present complex data insights to both technical and non-technical
stakeholders.
* Ability to work on-site at our Foothill Ranch, CA office, with a
collaborative and team-oriented mindset.

Profile Differentiators:

Startup and High-Growth Experience:
Demonstrated success working in fast-paced environments, especially as a
founder, co-founder, or early-stage team member where adaptability, innovation,
and execution were critical.

Industry Expertise in Powersports Finance:

Direct experience or strong familiarity with the powersports (motorcycles, ATVs,
UTVs, PWCs) finance industry, including knowledge of retail installment
contracts, dealer networks, and consumer behavior in the powersports segment.

Fintech Fluency:

Deep understanding of fintech trends, applications, and innovations,
particularly those that impact consumer lending, digital finance platforms,
alternative credit models, and automation in financial services.

Advanced SQL and Data Engineering Skills:

Expertise in writing optimized, complex SQL queries and working with large scale
relational databases. Experience with data wrangling, ETL processes, and
performance tuning.

Cloud and Data Pipeline Proficiency:
Hands-on experience with cloud-based platforms such as AWS, Azure, Snowflake,
Airflow. Also including tools like S3, Redshift, Glue, EMR, Azure Synapse, and
Data Factory.

Hybrid Technical & Strategic Mindset:

Ability to bridge the gap between deep technical analysis and high-level
business strategy, delivering insights that directly support revenue growth,
risk mitigation, and operational efficiency.

Strong Business Acumen:

Comfort operating at the intersection of data science, finance, and product
strategy, with an understanding of key business drivers and KPI’s in consumer
lending and asset-backed finance.

Entrepreneurial Spirit:

A self-starter mentality with a passion for building, optimizing, and scaling
data-driven systems and solutions from the ground up

Salary range: $110,000 - $115,000 annually, based on experience and
qualifications.

To support your health and wellness goals, Kawasaki provides a comprehensive
benefits program dedicated to the well-being of our employees and their
families. 

What We Offer: 

* Compet...

About Kawasaki Motors Corp., U.S.A.

Financial Services · 11-50 employees · founded 2025