Job Description

ROLE RESPONSIBILITIES

• 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

QUALIFICATIONS

• 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.