My Pfizer Experience: Estudiante en Practica - Data Analytics & AI Innovation

Commercial Excellence & Innovation (CEI)

Location: Bogotá (Hybrid / On‑site)

Duration: Internship (Full‑time preferred), 1 year.

Why Patients Need You

A career with us is about discovering innovations that change patients’ lives.
No matter your role, you will be part of bringing therapies to people around the world by enabling better, data‑driven decisions across the organization.

At Pfizer, data and analytics are critical tools to understand healthcare challenges, optimize decision‑making, and ultimately improve patient outcomes.

What You Will Achieve

As a Data Analytics & AI Innovation Intern within the Commercial Excellence & Innovation (CEI) team, you will support analytics, business intelligence, and AI‑enabled initiatives that directly inform commercial and strategic decisions.

You will work with real healthcare and commercial data, active Power BI dashboards, and cross‑functional stakeholders, contributing to:

• Improving data quality and analytical reliability

• Translating complex data into clear, actionable insights

• Supporting early AI and advanced analytics use cases in a regulated, enterprise environment

This role provides hands‑on exposure to how data, analytics, and AI are applied in real healthcare business contexts, beyond purely academic use cases.

What You Will Work On

Data Analytics & Visualization

• Support the development, maintenance, and improvement of Power BI dashboards used for commercial decision‑making

• Analyze datasets to identify data quality issues, inconsistencies, and improvement opportunities

• Translate business questions into structured analyses and visual insights, with guidance from CEI

Data Preparation & Programming

• Prepare data for analysis through cleaning, transformation, and classification

• Use Python, SQL, or similar tools to support: Data preparation and explorationAnalytical prototypingProcess optimization where applicable

• Work with structured and semi‑structured datasets in an enterprise environment

AI & Advanced Analytics Exposure

• Support analytics‑ and AI‑driven initiatives, including: Understanding and contributing to machine learning or predictive analytics projectsAssisting in the design, testing, or evaluation of AI‑ and agent‑based solutions

• Gain exposure to applied ML concepts, LLMs, and AI agents, with mentorship and business context provided

Stakeholder Interaction & Communication

• Collaborate with team members and stakeholders from different functions (commercial, data, digital)

• Support documentation, analytical summaries, and clear communication of results

• Participate in workshops, working sessions, and reviews when relevant

• Minimum B2-level English 

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Who Should Apply

Educational Background

We are particularly interested in students with a strong technical and analytical foundation, such as:

• Biomedical Engineering, Data Engineering, Industrial Engineering, Applied Mathematics, Statistics

• Or related fields with strong exposure to analytics and healthcare‑relevant problem‑solving

Technical Skills

• Strong foundation in Data Analytics

• Solid working knowledge of Power BI (data models, visuals; basic DAX is a plus)

• Experience using Python and/or SQL for data analysis and transformation

• Familiarity with BI, analytics, or data processing tools 

AI / ML Background (Preferred)

• Experience designing or executing machine learning or data science projects (academic, personal, or research‑based)

• Understanding of core ML concepts (e.g., features, models, evaluation)

• Interest in how AI and LLMs are used to solve real‑world healthcare or business problems

Interpersonal & Organizational Skills

• Clear, structured communicator, comfortable explaining analyses and asking good questions

• Able to work with multiple stakeholders and shifting priorities

• Organized, accountable, and able to manage tasks with guidance but without constant supervision

What Will Help You Succeed

• Curiosity and intellectual rigor

• Comfort navigating ambiguity in complex environments

• Ability to balance technical depth with practical business needs

• Openness to feedback and continuous learning

 
Work Location Assignment: Hybrid

EEO (Equal Employment Opportunity) & Employment Eligibility 

Pfizer is committed to equal opportunity in the terms and conditions of employment for all employees and job applicants without regard to race, color, religion, sex, sexual orientation, age, gender identity or gender expression, national origin, or disability.

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