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

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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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