Role Summary
Pfizer has established a chief digital office which will lead the transformation of Pfizer into a digital powerhouse that will generate superior patient experiences that will result in better health outcomes. If you thrive in a fast-paced environment that brings together scientific, clinical, manufacturing and commercial domains together through data and analytics then join the Artificial Intelligence, Machine Learning, Advanced Analytics and Data COE. Our collection of data scientists, business analysts and engineers are at the forefront of Pfizer's transformation into a digitally driven organization leveraging data and advanced analytics to change patient's lives.
As a Data Solution Specialist Manager you will be part of the Enterprise Data Solutions and Engineering team charged with designing, deploying, and continuously improving high quality, enterprise grade data products that power both advanced analytics/AI/ML and key business applications. You will engage with the analyst/ data science community to maximize the usefulness of our data and enable discovery, understanding and use of our key data products. You will be a member of a global team helping to progress commercial go-to-market strategies.
Role responsibilities
- Work with stakeholders across the organization to understand reporting, analytic, and application data needs
- Serve as the interface between business data users, analysts/ scientists, and engineers to create high value, enterprise grade data products
- Lead a cross functional data product development, deployment, and continuous improvement process through collaboration with a diverse team
- Liaise with senior leaders to obtain buy-in and funding to develop innovative products
- Maximize usability of assets through the creation of enablement and education of analyst/ data science/ application owners
Qualifications
- 5+ years of work experience managing a diverse range of data integration, analytics, and software projects
- Deep understanding of analyst and data science needs as it pertains to data availability, access, pipelining and AI/ ML applications
- Familiarity with various data storage paradigms including relational, unstructured, and graph and their associated use cases
- Experience with a wide array data science tools, methods, and platforms (Dataiku, Tableau, jupyter notebooks, etc.)
- Demonstrated ability to work effectively across cultures and to connect and engage with colleagues at all levels of the organization including the shop floor and the Pfizer leadership
- Demonstrated ability to make decisions quickly; shift direction with just enough information; and operate effectively in gray areas
- Demonstrated collaborative, consultative, problem solving, prioritization skills
- Demonstrated ability to simplify complex ideas for leadership and secure buy-in for innovative ideas
- Demonstrated experience educating and enabling analyst communities through continuous engagement
Basic Qualifications
- Bachelor's degree in Computer Science, Engineering, Life Science, Information Systems or related discipline
- Understanding of agile project approaches and methodologies (SAFE)
- Highly self-motivated to deliver both independently and with strong team collaboration.
- Strong aptitude for learning new technologies and analytics techniques.
Preferred qualifications
- Experience with leading projects (data integration, software, analytics) in a cloud-based ecosystem (AWS, Snowflake, etc)
- Previous experience within life sciences analytics or data organizations
- Knowledge of life sciences global availability and useability of data: public/ open source/ internal, RWD, manufacturing, commercial etc.
- Hands on experience working in Agile teams, processes, and practices
- Experience working in a regulated environment i.e. SOX, GXP and life science related privacy and compliance implications
- Demonstrated ability to solve business problems through the collection of data and application of AI/ ML principles