Capgemini Technology Services

FBS - Predictive Analyst I

Brazil full-time Entry Salary not listed
full-time Entry level Technology & IT Curated
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About the role

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.
Originally posted on Himalayas

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Entry
Technology & IT API integration Data Analysis Finance Human Resources MySQL Entry level

Likely questions

  1. Tell us about work you have done that is close to the FBS - Predictive Analyst I role.
  2. How would you approach your first 30 days at Capgemini Technology Services?
  3. Which of API integration, Data Analysis and Finance have you used recently, and what did it help you achieve?
  4. What have you learned quickly in a past role, project, or training experience?
  5. How do you handle busy days, changing priorities, or pressure at work?

Prepare before the call

  • A recent example that proves your experience with API integration, Data Analysis and Finance.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the FBS - Predictive Analyst I role because I can bring practical experience in API integration, Data Analysis and Finance, learn the team quickly, and contribute to the outcomes Capgemini Technology Services needs from this hire.

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