Suba, Bogota, Colombia
8 hours ago
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 

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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