20 publicaciones de empleo destacadas de machine learning platform en centro (área 1), dif (¡Están contratando!)

Manager, Commercial Performance Analytics.
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Manager, Commercial Performance Analytics.

Pfizer -
Ciudad de México, CDMX

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Información del empleo

Tiempo completo

Cualificaciones

Power BI
Administración de personal
R
Tableau
Maestría
Experiencia en bases de datos
SQL
Licenciatura
Visualización de datos
Habilidades de comunicación
Python

Descripción completa del empleo

Work Location Assignment: Mexico City, must be able to work from assigned Pfizer office 2-3 days per week, or as needed by the business.

ROLE SUMMARY

Commercial Analytics harnesses the power of data to drive robust analytical insights that inform some of Pfizer’s most critical business questions. With colleagues across the globe, the Commercial Analytics team’s rigorous analytical expertise is depended on as the compass for decision support across the enterprise. Our dynamic, exciting team of subject-matter experts comes from diverse backgrounds and experiences, including data science, commercial analytics, finance, market research, and consulting. As a team, we collaborate to turn data into meaningful insights that will have a direct impact on patients’ lives and the future of Pfizer as a data-driven organization.

We are seeking a Manager, Commercial Performance Analytics to serve as a hands-on individual contributor within our Mexico City analytics capability center, building the datasets, pipelines, and analytical assets that power performance tracking and insight generation for the commercial organization. This role designs and automates scalable analytics solutions in SQL, Python, and R, while partnering closely with US-based Performance Analytics and Insights (PAI) colleagues as its primary point of collaboration. Working from PAI-defined priorities, the successful candidate will help standardize and centralize the commercial analytics and reporting ecosystems and implement industry best practices in performance analytics and insight-generation processes.

This role is dynamic, fast-paced, highly collaborative, and covers a broad range of strategic topics that are critical to our business. The successful candidate will join Global Commercial Analytics (GCA) colleagues worldwide who are dedicated to driving business through proactive thought leadership, innovative technical capabilities, and the ability to communicate complex and dynamic information in new and creative ways.

ROLE RESPONSIBILITIES

Technical Development & Analytics Solutions

Design, develop, and maintain scalable analytics solutions using SQL, Python, R, and related technologies.

Build, optimize, and automate datasets, data pipelines, and reporting frameworks to support commercial performance measurement.

Engineer and integrate data from multiple internal and external sources to create robust analytical datasets.

Develop and maintain high-quality analytical assets, including dashboards, reporting tools, and reusable code libraries.

Improve performance, reliability, and scalability of existing analytics workflows through automation and process optimization.

Leverage AI, scripting, and emerging analytical technologies to increase efficiency and analytical capabilities.

Analysis & Insight Generation

Perform advanced analyses on patient, HCP, payer, and commercial datasets to identify trends, opportunities, and risks.

Apply statistical, quantitative, and machine learning techniques to solve business problems and generate actionable insights.

Conduct data quality assessments, validation, and troubleshooting to ensure accuracy and consistency of analytical outputs.

Translate complex analytical findings into clear insights supported by quantitative evidence.

Collaboration & Partnership

Partner closely with US-based PAI colleagues as the primary point of collaboration, supporting shared analytics priorities and delivering against team-defined requirements.

Translate information needs surfaced by PAI leads into robust analytical solutions, connecting datasets to tell a clear, compelling story backed by quantitative evidence.

Work with PAI and broader analytic functions to advance the use of novel data sources and improve reporting processes, tools, and standards.

BASIC QUALIFICATIONS

• Bachelor’s degree (Master’s preferred) in a quantitative discipline such as computer science, engineering, economics, statistics or related field.

5+ years of experience in Biopharma, analytics, strategic healthcare consulting, or related fields.
Extensive expertise in SQL, Python, R, or similar; other object-oriented programming languages. Advanced knowledge of scripting tool and creation of AI agents for automation.
Understanding of data visualization tools and experience designing and building complex dashboards, including but not limited to Tableau, PowerBI, Qlik and similar.
Analytics, statistics and/or database knowledge and experience (using tools, applications, platforms, etc.).
Hands on experience in data types/formats, data architecture, pipeline/ETL optimization
Knowledge of data cloud platforms like Snowflake preferred.
Strong Project Management Skills: Overseeing complex, cross-functional projects, ensuring delivery on time and within budget.
Collaboration: Ability to prioritize, and developing action plans.
Communication: Strong written and verbal communication skills.

PREFERRED QUALIFICATIONS

Recent Healthcare Life Sciences (pharma preferred) and ecosystem professional industry experience is preferred; commercial analytics experience is a plus.

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.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.

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machine learning platform empleos en centro (área 1), dif

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