Job Description

+ Work closely with business & BT teams across Pfizer China to maximize the use of data in answering key questions related to: acceleration of drug discovery efforts, identification of drug repurposing opportunities, optimization of clinical trial activities, improving patient access to Pfizer therapies through a better understanding of outcomes & patterns of care, and maximizing the value of our interactions with patients, healthcare providers, payers, and regulatory agencies.
+ Partner closely with local Business Technology teams to define and execute POCs using innovative technologies to advance Pfizer's analytics and AI capabilities
+ Lead rapid-prototyping engagements focused on assessing use case viability and gauging potential business impact
+ Partner closely with the global AI CoE team to define & champion common AI-enabled solution architecture for use across the enterprise
+ Provide technical leadership in the delivery of analytics and AI pipelines that include components related to data acquisition, exploratory analysis, feature engineering, predictive model design/build and interactive storytelling.
+ Shared-ownership of advancing the team's analytics and AI capabilities through implementation and execution of state-of-the-art approaches
+ Produce actionable data presentations and visualizations for decision makers throughout the organization
+ Directly engage with key business stake-holders (Sr. Director/Director level)
+ Leadership of multiple project teams comprised of colleagues & contract staff
+ Provide leadership & regional representation of AI CoE's global team across the China/APAC region
+ Partner with global AI engineering team to drive adoption of micro services framework across AI projects within the China /APAC region
Identify & implement reusable components (Micro Services) across multiple projects leveraging common solution patterns
+ 8+ years' experience leading analytics or AI projects teams and building analytical platforms in a large organization with multiple functional constructs
+ 5+ years' experience working as a data scientist / ML engineer
+ 3+ years working with semi-structured and unstructured data
+ 2+ years working in a cloud based analytics ecosystem
+ Advanced degree in Computer Science, Operations Research, Data Science, Applied Mathematics or related field
Proven experience in at least two of the three following categories:
+ Data Science / Machine Learning
+ Expertise with general-purpose statistics/machine learning algorithms and at least one of the following sub-disciplines: Natural Language Processing, Deep Learning, Network Analysis.
+ Expertise with the implementation of algorithms within Python, Spark, R, or Scala
+ Expertise with model tuning, validation and evaluation
+ Data Engineering
+ Experience with SQL development, database administration and performance tuning
+ Experience with data manipulation and extraction using modern programming languages (Java, C++, C#, Python, Scala, Spark, etc.)
+ Experience with Unix/Linux development - package management, knowledge of filesystems, performance monitoring/troubleshooting
+ Experience with NoSQL databases (MongoDB, Cassandra, etc.)
+ Machine Learning Engineering
+ Experience building production implementations of data science and engineering pipelines
+ Experience developing production-grade components within a larger ecosystem
+ Experience with sourcing data from APIs; experience building APIs is a plus
+ Ability to create technical examples, prototypes, and demonstrations based on rapidly changing data sets
+ Ability to thrive in a fast-paced multi-disciplinary environment; with the ability to effectively communicate with a diverse audience
+ Ability to communicate the results of complex analysis to non-technical audiences via effective visualizations and presentations
+ Excellent written and verbal communication skills
Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.