Solutions
Recruitment Software
Post jobs, import profiles, add screening questions, and manage hiring all in one place with personalized questions and control the entire recruitment process.
Recruitment Service
Let our expert team handle the key stages of tech recruitment for you with our specialized team acting in the main stages of recruitment.
Talent Pool
Top-tier Brazilian tech professionals, pre-vetted and ready for action, all pre-selected and ready for new opportunities.
Our Plans
Discover the perfect plan for your needs.
Use Cases
Build my own team
Define the profile, validate with our experts, and assemble your tech team with full control over every step.
Autopilot
Put tech recruitment on autopilot and receive pre-vetted candidates matched to your needs without lifting a finger.
Complete Solution
From sourcing to hiring — an end-to-end tech recruitment experience powered by AI, specialists, and a curated talent pool.
Why Geekhunter?
Resources
HR Blog
Contents about people management, organizational culture and trends in human resources.
Glossary
A comprehensive guide to the key terms and concepts in tech recruitment and software development.
Frequently Asked Questions
Clear answers to the most common questions about using the platform and recruitment processes.
EN
Hybrid
São Paulo - SP
Salary Range
Not informed
Experience Level
Leader/Coordinator
Requirements
Tasks and Responsibilities
Show originalAbout the Opportunity:
We are seeking a Data Science Specialist to work strategically within our Auto Pricing and Analytics area. This is a high-visibility role for professionals who want to be key drivers in value generation, leading the development of complex predictive models, experimentation, and the creation of new analytical features applied to the business.
If you have strong analytical thinking, a passion for solving complex business problems through data, and want to transform the insurance market, this role is for you.
Key Responsibilities:
- Advanced Modeling: Develop predictive and statistical models focused on pricing (GLMs and Machine Learning), propensity, acceptance, and fraud prevention.
- Feature Engineering: Build advanced features from large volumes of internal and external data (geospatial, behavioral, and market data).
- Strategic Pricing: Support the construction, calibration, and maintenance of tariff models and business rules in production environments.
- Experimentation and Validation: Develop and monitor A/B tests to validate model impact, ensuring statistical consistency between exploratory and production environments.
- Business Acumen: Translate business pain points (loss ratios, conversion, retention) into structured analytical solutions and convert technical insights into executive recommendations.
- Collaboration and MLOps: Partner with data engineering teams for the deploy, monitoring, and operationalization of models via analytical pipelines.
Requirements and Qualifications
Academic Background: Completed higher education in quantitative fields (Statistics, Mathematics, Engineering, Computer Science, Economics, or related areas).
Technical Knowledge
- Strong experience in Machine Learning (tree-based models, boosting, neural networks) and statistical modeling.
- Advanced proficiency in Python and SQL.
- Experience with Databricks (PySpark, MLflow, notebooks, Delta Lake).
- Hands-on experience with large data volumes, model metric evaluation, and A/B testing.
- Understanding of MLOps and integration between analytical models and tariff models.
- Relevant advantage: Previous experience in the insurance/reinsurance sector.
- Technical advantage: Familiarity with actuarial pricing software (such as the WTW suite - Emblem and Radar).
Share job:
Share job: