Intern supporting the development of AI applications and models for vehicle distribution. Collaborating with an agile product team at BMW in Munich.
About the role
- Senior Data Scientist leading advanced data modeling initiatives to automate and transform processes at Farmers. Collaborating with business leaders to deliver AI/ML solutions that enhance efficiency and decision-making.
Responsibilities
- Lead the design, build, and validation of quantitative models (descriptive, predictive, optimization/simulation) for underwriting automation and other business functions.
- Develop and deploy ML solutions that accelerate quote-to-bind processes, automate risk assessment, and enable straight-through processing for standard risks.
- Create sophisticated risk and customer segmentation strategies; build real-time scoring engines to support instant decisioning.
- Pull, clean, and manage datasets; design models using advanced statistical and machine learning concepts (e.g., regression, GLMs, decision trees, ensemble modeling etc.).
- Own business outcomes (OKRs and KPIs) and communicate results and insights to business leaders and stakeholders.
- Perform research and development on new algorithms, modeling concepts, and technical tools; recommend adoption of new approaches into our analytics toolkit.
Requirements
- 5-7 years as Data Scientist or related technical role in a delivery oriented environment required.
- Experience within the insurance industry and insurance data preferred.
- 5-7 years of experience building and deploying machine learning models in production environments with proven track record of building models that impact business KPIs
- Advanced proficiency in Python and ML frameworks (scikit-learn, XGBoost, TensorFlow, PyTorch).
- Expert proficiency in data management programming (SQL) and real-time data processing pipelines.
- Experience integrating and working with third-party data APIs and ETL pipelines.
- Strong written and oral communication skills; ability to present to senior executives and non-technical stakeholders.
- Well-organized and able to lead projects from a technical standpoint.
- Experience leading projects using CRISP-DM or similar frameworks.
- Experience with insurance data and industry-specific modeling.
- Knowledge of AI-powered development tools (e.g., GitHub Copilot) for accelerated model development.
- Proven expertise in processing automation and workflow optimization using ML/AI.
- Mastery of advanced statistical and machine learning concepts, including regression, GLMs, decision trees, ensemble modeling, clustering, and SVM.
Benefits
- Bonus Opportunity (based on Company and Individual Performance)
- 401(k)
- Medical
- Dental
- Vision
- Health Savings and Flexible Spending Accounts
- Life Insurance
- Paid Time Off
- Paid Parental Leave
- Tuition Assistance
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