My Pfizer Experience: Estudiante en Practica
Healthcare
EstudianteenPractica-DataAnalytics&AIInnovation
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“Estudiante en Practica - Data Analytics & AI Innovation at My Pfizer Experience: Estudiante en Practica. Skills: Data Analytics, Business Intelligence, AI Innovation, Power BI, Python, SQL. Support analytics, business intelligence, and AI-enabled initiatives. Improve data quality and analytical reliability”
What You'll Achieve.
Enabling better, data-driven decisions across the organization; Improving patient outcomes; Informing commercial and strategic decisions; Improving data quality and analytical reliability; Translating complex data into clear, actionable insights; Supporting early AI and advanced analytics use cases
Industry & Context.
Translating complex data into clear, actionable insights; Healthcare-relevant problem-solving
What They're Looking For.
Must Have
Strong technical and analytical foundation, Data Analytics foundation, Power BI, Python, SQL, B2-level English
Nice to Have
Basic DAX, Machine learning or data science projects experience, Core ML concepts understanding, Interest in AI and LLMs for healthcare/business problems
What You'll Do.
business intelligence
and AI-enabled initiatives
Improve data quality and analytical reliability
Translate complex data into clear
Support early AI and advanced analytics use cases
Support the development
and improvement of Power BI dashboards
Analyze datasets to identify data quality issues
and improvement opportunities
Translate business questions into structured analyses and visual insights
Prepare data for analysis through cleaning
or similar tools to support data preparation and exploration
analytical prototyping
and process optimization
Work with structured and semi-structured datasets
Support analytics- and AI-driven initiatives
or evaluation of AI- and agent-based solutions
How You'll Work.
Team & Collaboration
Collaborate with team members and stakeholders from different functions (commercial, data, digital); Participate in workshops, working sessions, and reviews
Communication Scope
Clear communication of results; Clear, structured communicator; Comfortable explaining analyses; Asking good questions
Process & Methodology
Manage tasks with guidance but without constant supervision
Full Job Description
# **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
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