Manager, Machine Learning

hace 4 semanas

Tlahuac, México Pfizer A tiempo completo

ROLE SUMMARY
- Do you want to make an impact on patient health around the world? Do you thrive in a fast-paced environment that brings together scientific and clinical domains together through data and analytics? Then join Pfizer Digital’s Analytics, Data and Learning organization where you can leverage cutting-edge technology including AI and ML to inform critical business decisions and improve customer experiences for our patients and physicians. Our collection of global teams drives insights to action for some of the most critical business questions for the company. Our analytics professionals are based in over 30 countries around the world and come from diverse backgrounds including: market research, data science, digital analytics, finance, investment banking, corporate development, and consulting. Join one of our teams and be at the forefront of Pfizer’s digital transformation, driving innovation and bringing advance analytics to change patients’ lives._

ROLE RESPONSIBILITIES
- Design, develop and deploy machine learning products & approaches to solve business problems across commercial and medical affairs domains
- Engage with stakeholders across the enterprise to understand and solve complex problems through AI/ML and inform business strategy and decisions
- Design and execute advanced analytics and predictive modeling projects using rigorous statistical methods and machine learning techniques
- Design, develop, deploy and maintain reusable assets and custom pipelines to optimize operational efficiencies in analytics execution
- Lead Agile-based project management standards (i.e. daily check-in procedures, workload status, and cost overruns/projections)
- BASIC QUALIFICATIONS
- 5-6_ years of work experience as a machine learning engineer or data scientist and project lead for a diverse range of projects_
- _ 3 years of project and stakeholder management experience_
- _ STEM (Science, Technology, Engineering, Mathematics) majors with quantitative emphasis - Statistics, Computer Science, Economics, Engineering etc._
- _ Expert proficiency in R, Python, and analytics platforms w_ith expertise in machine learning libraries (e.g., scikit-learn, TensorFlow, Keras)._
- _ Applied knowledge of statistical analysis, experience with R, Excel, etc._
- _ Strong background in computer science: algorithms, data structures, machine learning, and distributed systems_._
- _ Superior analytical skills required; Strong verbal and written communication skills_
- _ Demonstrated experience interfacing with other internal and external teams to incorporate their innovations and vice versa_- PREFERRED QUALIFICATIONS
- Advanced understanding of machine learning algorithms, deep learning architectures, and statistical techniques with a focus on forecasting.
- Experience with foundation models, LLMs, or other areas of generative AI.
- Proficiency in data preprocessing, feature engineering, and dimensionality reduction.
- Familiarity with software engineering principles (e.g. version control, testing, and deployment)
- Knowledge of cloud platforms (AWS, GCP, Azure) and distributed computing frameworks (e.g., Spark) is a plus.
- Industry or consulting experience, along with project management skills preferred
- Experience in one or more of the following areas preferred: machine learning, statistics, healthcare, life sciences
- Experience working in Agile processes and practices

LI-PFE

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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