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Master's Fellow – Statistics, Predictive Models, Python, AWS

Job not on LinkedIn

🕒 August 14

🇧🇷 Brazil – Remote

💵 R$9k / month

⏰ Full Time

🟡 Mid-level

🟠 Senior

🔙 Backend Engineer

🗣️🇧🇷🇵🇹 Portuguese Required

Where this job comes from

Posted on Sistema Fibra's careers page, not through a job board

First seen by Remote Rocketship August 14

Still open on Sistema Fibra's site. Checked 54 minutes ago.

Logo of Sistema Fibra

Sistema Fibra

1001 - 5000 employees

Founded 1972

🤝 B2B

🤝 Non-profit

📚 Education

B2B • Non-profit • Education

Sistema Fibra is a civic organization based in Brasília that focuses on enhancing the competitiveness of industries and entrepreneurship through representation and support. It brings together various entities, including Sesi, Senai, and IEL, to promote industrial growth and workforce development in Brazil.

📋 Description

• Understand the IFRS 17 standard regarding risk adjustment • Assess current practices for measuring the Risk Adjustment under IFRS 17 • Identify critical variables, such as claims volatility, cancellations, expenses, and lapses, and the available internal data sources • Justify the statistical model methodology used for the risk adjustment • Perform consistency tests to maintain the statistical model for the risk adjustment • Prepare documentation and provide support for internal and external audits

🎯 Requirements

• Completed Master's degree • Degree or coursework in Statistics and Actuarial Science • Knowledge of probability and probability distributions • Knowledge of regression analysis, factor analysis, and time series • Programming in Python or experience with AWS services/applications • Knowledge of IFRS 17 (desirable) • Knowledge of technical provisions for private pension plans and BRGAAP (Brazilian GAAP) regulatory standards (desirable) • Availability for 40 hours per week

🏖️ Benefits

• Gross monthly stipend of BRL 9,000 • Duration of 8 months with possibility of stipend renewal • Remote work (home office) • Availability for 40 hours per week

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