Senior Data Scientist

About Us

Dealer Owned Warranty Company LLC is a leading provider of F&I (Finance and Insurance) partnership services in the automotive industry, offering a full suite of obligor and administrator services, top-of-the-line products, technology, and training. We understand the importance of leveraging process and technology in the F&I industry to drive revenue and ensure success. Our goal is to provide visibility, transparency, and the tools needed for our partners to build their wealth and achieve their goals. We are located in Parsippany, NJ - only seeking local candidates at this time.

Please double check you have the right level of experience and qualifications by reading the full overview of this opportunity below.

Job Summary:

The Senior Data Scientist (Actuarial) is a senior, highly experienced individual contributor responsible for designing, building, deploying, and maintaining advanced analytics and machine learning solutions that drive business performance across the organization. This role is embedded within the business and focuses on applied data science—not academic or exploratory research. The Senior Data Scientist partners closely with stakeholders across Underwriting, Claims, Finance, Operations, and Dealer Services to translate complex business problems into scalable, explainable, and production-ready analytical solutions. This role exercises independent judgment, technical leadership, and business acumen to improve profitability, reduce risk, and enhance operational efficiency across the full product lifecycle.

Duties/Responsibilities:

• Own end-to-end data science initiatives, including problem definition, data exploration, feature engineering, model development, validation, deployment, and ongoing monitoring.
• Partner with Finance, Claims, Operations, Underwriting, and Dealer teams to translate business objectives into analytical solutions and decision frameworks.
• Build and deploy production-grade models, including but not limited to risk scoring, fraud detection, forecasting, segmentation, and optimization models.
• Develop models to improve claims outcomes, loss ratios, and fraud detection while balancing accuracy, interpretability, and operational usability.
• Create financial forecasting, scenario analysis, and planning models used by leadership for performance management and strategic decision-making.
• Analyze and segment dealer performance to support profitability analysis and partner strategy.
• Improve data quality and reliability by developing solutions for data validation, anomaly detection, and entity resolution.
• Design and evaluate experiments, including A/B testing and causal analysis, to measure business impact and inform decision-making.
• Define, operationalize, and monitor key business and model performance metrics in collaboration with Business Intelligence (e.g., Microsoft Power BI).
• Ensure models are scalable, well-documented, explainable, and monitored for performance degradation, bias, and drift.
• Collaborate closely with Data Engineering to integrate models into data pipelines and production systems using tools such as Snowflake, Python, Airflow, and dbt.
• Mentor and support junior data science team members and contribute to data science standards, best practices, and documentation.
• Ensure the responsible, secure and compliant use of data and outputs in accordance with company standards, privacy requirements and regulatory obligations.
• Perform additional duties as assigned to support data and organizational objectives.

Required Skills/Abilities:

• Advanced proficiency in Python for data analysis and machine learning; pandas, scikit-learn, PyTorch or TensorFlow a plus.
• Advanced SQL skills with a strong understanding of relational data modeling and querying large datasets.
• Experience deploying models into production environments
• Strong working knowledge of statistical modeling, machine learning, and analytical techniques, including: Experimentation and causal inference, Predictive modeling (classification and regression), Time-series forecasting, Anomaly detection
• Solid understanding of data pipelines, ETL/ELT processes, and modern data architectures.
• Experience working with modern data stacks and cloud-based data warehouses (e.g., Snowflake, dbt, Airflow).
• Strong analytical, critical-thinking, and problem-solving skills.
• Excellent verbal and written communication skills, with the ability to explain complex concepts to non-technical stakeholders.
• Ability to work independently, manage multiple priorities, and exercise sound judgment in a fast paced environment.

Education and Experience:

• Bachelor’s degree in Data Science, Actuarial Science, Statistics, Mathematics, or Engineering or related field required; Master’s degree preferred.
• Actuarial credentials or passed actuary exams.
• 10+ years of experience in data science, applied machine learning, or advanced analytics, with demonstrated experience delivering business-impacting solutions.
• Prior experience partnering directly with business stakeholders required.
• Experience in financial services, insurance, underwriting, claims, or risk-related domains preferred.

Come join our growing team here in Parsippany! As NJs Best Places to Work Honoree for four years in a row, we offer:

• Competitive compensation
• PTO and Sick Time
• Medical, Dental, Vision, 401k matching, Life Insurance, Ancillary Benefits
• Full-service cafeteria on-site serving breakfast & lunch from an exclusive private chef.
• Corporate events, team and culture building activities, employee awards and recognition, company trips and more!

DOWC (and its affiliated brands) is an Equal Opportunity/Affirmative Action employer. xihmbke All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected Veteran status, sexual orientation, gender identity, gender expression, genetic information, or any other characteristic protected by law. Applicants who require accommodation to participate in the job application process may contact us for assistance.