Sobre esta vaga de FBS - Predictive Analyst I na Capgemini
Farmers Insurance is one of the United States’ largest insurers, providing a wide range of insurance and financial services products with gross written premiums well over US$25 Billion (P&C). They proudly serve more than 10 million U.S. households with more than 19 million individual policies across all 50 states through the efforts of over 48,000 exclusive and independent agents and nearly 18,500 employees. Finally, Farmers Insurance is part of one the largest Insurance Groups in the world.
About the Role
We are seeking a Predictive Analyst I to join our Finance Data & Analytics team and support data-driven decision-making through predictive modeling and advanced analytics. This role will focus on developing and implementing statistical and machine learning models to identify trends, generate insights, and support business and financial outcomes.
The ideal candidate combines strong analytical and technical skills with the ability to translate complex data and modeling results into clear, actionable recommendations for business stakeholders. You will work with large datasets, contribute to predictive modeling initiatives, and collaborate with cross-functional teams to continuously improve analytical solutions and data practices.
What You’ll Do
- Develop and implement predictive models using statistical and machine learning techniques such as regression, clustering, decision trees, and neural networks
- Prepare, structure, and analyze large datasets from internal and external sources for modeling and analytics
- Build and maintain programs for predictor and response variables, ensuring model accuracy, scalability, and reliability
- Partner with business stakeholders to understand business challenges and translate them into analytical solutions
- Analyze data to identify trends, patterns, opportunities, and potential business impacts
- Present analytical findings and recommendations to technical and non-technical audiences
- Explain modeling methodologies, data sources, assumptions, and results in a clear and business-focused manner
- Perform data validation and quality checks to ensure data integrity and model reliability
- Contribute to the development and continuous improvement of predictive modeling frameworks, processes, and best practices
- Develop knowledge of the organization's data landscape, including data sourcing, mapping, transformation, and integration across systems
- Support enterprise data initiatives, including data migration and transformation projects
- Collaborate with other analysts, data scientists, and business partners to deliver analytical solutions
- Share knowledge and best practices with junior team members and contribute to a collaborative learning environment
Requirements
- Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Business Analytics, or a related discipline
- Master's degree is preferred
- Strong foundation in statistics, predictive modeling, and machine learning concepts
- Experience working with large datasets and performing data preparation, transformation, and analysis
- Experience developing and validating predictive or statistical models
- Programming experience in Python, R, SQL, or similar analytical languages
- Strong analytical and problem-solving skills
- Ability to communicate technical concepts and analytical findings clearly to non-technical stakeholders
- Strong attention to data quality, model accuracy, and analytical rigor
- Ability to work collaboratively with business, technical, and analytics teams
- Experience or interest in insurance analytics, financial analytics, or predictive modeling is preferred
- Fluent English communication skills required
Benefits
- Comprehensive benefits package
- Career development and training opportunities
- Flexible work arrangements
- Dynamic and inclusive work culture within a globally renowned group
- Private Health Insurance
- Pension Plan
- Paid Time Off
- Training & Development
Please note: CVs must be submitted in English. Applications submitted in other languages will not be considered.
• Personal Data Processing: The personal data provided during the recruitment and selection process will be collected, processed, and retained for legitimate recruitment and compliance purposes, in accordance with applicable data protection and privacy laws and FBS internal policies.
• Legal Authorization to Work: Employment with FBS is conditional upon the candidate having valid, local legal authorization to work in the country where the role is based at the time of hire. FBS does not sponsor or obtain work authorization unless explicitly stated.
• Exclusivity of Employment and Conflict of Interest: Upon acceptance of an offer and during employment with FBS, employees will not be permitted to engage in parallel employment, professional activities, or paid work for other entities. Any ownership, partnership, directorship, or participation in other businesses or companies must be fully disclosed and formally reviewed in accordance with FBS internal conflict‑of‑interest and external engagement policies prior to the start date or as soon as such circumstances arise.
Failure to comply with these conditions may impact the hiring decision or employment continuation.
