Data Scientist

As a Data Scientist, you will play a critical role in developing and maintaining data pipelines, models, and insights that bridge the gap between engineering and business. Your contributions will drive the evolution of data services, enabling the creation of cutting-edge products and services.

Key Responsibilities:

• Collaborate with insurance domain experts and engineering teams to predict insurance claims using advanced data science techniques and hundreds of variables.
• Develop new data sources (e.g., web scraping, public/private APIs) that minimize development cycles while maximizing business applications.
• Innovate and refine underwriting processes to improve accuracy and efficiency, reducing the number of application questions.
• Maintain a clean, production-ready data environment, ensuring models are interpretable and accessible for data science and engineering team members.
• Present findings and recommendations to both technical and non-technical stakeholders.
• Build and support a team of data scientists and analysts to accelerate learning and elevate product offerings.

What Were Looking For:

• Bachelors or Masters degree in a quantitative discipline (e.g., Computer Science, Mathematics, Statistics, Economics, Physics, Engineering, or a related field).
• 3+ years of experience as a Data Scientist, Data Analyst, or in Machine Learning roles.
• Proven experience training and deploying machine learning models to drive business decisions.
• 5+ years of Python experience, including working with the data science stack (e.g., pandas, scikit-learn, numpy, scipy, Jupyter).
• Strong understanding of data science metrics and methodologies for evaluating model performance.
• Hands-on experience tracking model performance in production.
• Expertise in building clean, repeatable experiments in a notebook environment.
• Excellent communication skills to translate technical analysis into actionable business recommendations.
• Familiarity with scaling data infrastructure and database systems, understanding the tradeoffs involved.
• A proactive, creative approach to using data with a bias toward practical action (portfolio or project examples are a plus).

Non-Negotiables:

• Proficiency in Python, ideally with experience using the data science stack (e.g., scikit-learn, pandas, numpy).
• Experience building machine learning models that have been used for tangible business decision-making.
• Experience using analytics to identify patterns in large datasets within a business context.
• Ability to evaluate model performance in the context of business metrics (beyond standard metrics like AUC, precision, recall).
• Basic SQL knowledge and experience with reporting tools.
• Familiarity with JSON.
• Experience with Git or version control systems.

Why Join Us?

• Full-time position
• Payment in US dollars
• Contractor hiring mode
• 100% remote anywhere in LATAM
• Holidays from your country off and paid
• Birthday off and paid
• Career Path
• Recognition Program
• Paid Leaves

If you are interested in applying for this position and meet the specified requirements, please let us know. We look forward to the possibility of working with you.