Associate Analyst, Data Science

Liberty Specialty Markets Latam; Bogotá; Presencial; COP 24.000.000 - 48.000.000; Jornada completa

Descripción de la vacante

Liberty Specialty Markets Latam is launching a Data Science hub in Bogotá. We seek analysts to build a high-impact data function, collaborate globally, and automate ML pipelines for business insight in insurance and financial services.

You will work with large datasets, develop predictive models, and communicate results to stakeholders while expanding domain expertise in insurance and financial services within a collaborative team.

Formación

• Fluency in English at C1 level is required.
• Bachelor’s degree in Mathematics, Statistics, Computer Science, Economics, Actuarial Science, or related quantitative field.

Responsabilidades

• Apply data science techniques to explore, manipulate, and analyze large datasets to uncover insights and support business decisions.
• Collaborate on development and validation of predictive models (GLMs, decision trees, other ML) aligned with business objectives.
• Formulate and test hypotheses with statistical rigor.
• Translate findings into clear visualizations and narratives for diverse audiences, including business stakeholders.
• Contribute to moderately complex projects, tailoring analytic approaches to business needs and operations.
• Engage with global Data Science community to promote innovation and best practices.
• Build domain knowledge in insurance and financial services to enhance impact.

Conocimientos

English C1

Bachelor's degree (quant)

0-2 years or Master

Data extraction

EDA

Data transformation

Predictive modelling

GLM

Decision trees

Analytical skills

Communication skills

Educación

Bachelor’s degree in quantitative field

Master degree (optional)

Herramientas

NA

Descripción del empleo

The Data Science Solutions team is launching a new global hub in Colombia and seeks talented data science analysts to build a vibrant, 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 that solve real-world business problems.


• Work with large structured and unstructured datasets to uncover patterns, build models, and generate actionable insights.


• Contribute to automating and scaling machine learning pipelines, model monitoring, and performance improvements.


• Communicate findings clearly to technical and non-technical stakeholders to drive data-informed decisions.


• Expand your insurance domain knowledge while deepening your expertise in data science and MLOps.


• Join a foundational team, gain exposure to end-to-end model operations, and grow your career in a collaborative, innovative-driven environment.

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:

• Fluency in English C1 (Must)


• Bachelor’s degree in Mathematics, Statistics, Computer Science, Economics, Actuarial Science, or a related quantitative field.


• 0-2+ year experience or Master Degree relevant for the role.


• Solid foundation in data extraction, exploratory data analysis (EDA), data transformation, and predictive modelling techniques such as GLM and decision trees, traditional ML.


• 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.


• Candidates should demonstrate strong business acumen and the ability to quickly learn the insurance domain.


• 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.