About the Role:
- The Data Science Solutions team is excited to launch a new global hub in Colombia and is looking for talented data science analysts to help shape a vibrant and high-impact function from the ground up.
- As an Analyst in the Model Automation & Production team, you will:
- Collaborate with global colleagues to develop predictive analytics to solve real-world business problems.
- Work hands-on with large structured and unstructured datasets to uncover patterns, build models, and generate actionable insights.
- Contribute to the automation and scaling of machine learning pipelines, model monitoring, and performance enhancements.
- Communicate findings clearly to technical and non-technical stakeholders, helping drive data-informed decisions.
- Expand your knowledge of the insurance domain while deepening your technical expertise in data science and MLOps.
- This is a unique opportunity to be part of a foundational team, gain exposure to end-to-end model operations, and grow your career in a collaborative, innovation-driven environment.
About the Team and Department:
- Data Science Solutions develops predictive analytics that empower data-driven strategic decisions across the business. By leveraging both established and emerging data science techniques, we work with large structured and unstructured datasets to uncover insights and build models that drive meaningful business outcomes.
- Within this group, the Model Automation & Production team focuses on maximizing the value of our existing models through efficiency and automation.
Our responsibilities include:
- Model monitoring, refresh, and enhancement
- Development and maintenance of machine learning data pipelines
- Management of data science infrastructure
- Promotion and implementation of data science best practices
- Together, we ensure that our models remain robust, scalable, and impactful.
Key Responsibilities:
- Apply data science techniques to explore, manipulate, and analyze large structured and unstructured datasets to uncover insights and support business decisions.
- Collaborate on the development and validation of predictive models, including GLMs, decision trees, and other machine learning approaches, aligned with business objectives.
- Formulate and test hypotheses with statistical rigor, ensuring reliability and relevance of analytical outcomes.
- Translate complex quantitative findings into clear visualizations and compelling narratives for diverse audiences, including business stakeholders.
- Contribute to projects of moderate complexity, customizing analytic approaches to meet specific business needs and operational goals.
- Engage with the global Data Science community, participating in cross-functional initiatives and knowledge-sharing forums to promote innovation and best practices.
- Build and apply insurance and financial services domain knowledge to enhance the impact and relevance of your work.
Skills and Experience:
- Bachelor’s degree in Mathematics, Statistics, Computer Science, Economics, Actuarial Science, or a related quantitative field; Master’s degree or equivalent industry experience (2-3 years) preferred.
- Solid foundation in data extraction, exploratory data analysis (EDA), data transformation, and predictive modelling techniques such as GLM and decision trees.
- Strong analytical and problem-solving skills, with the ability to work with large datasets and derive meaningful insights.
- Effective oral and written communication skills, with the ability to present complex findings clearly to both technical and non-technical audiences.
- Collaborative mindset and interpersonal skills to work effectively within cross-functional teams and global environments.
- Interest or experience in insurance, financial services, or fintech, with a desire to deepen domain knowledge.
- Proficiency with data science tools and programming languages such as Python, SQL, and version control systems (e.g., Git).
- Fluency in English and Spanish LEVEL B2-C1
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