Pfizer’s Chief Digital Office (CDO) leads the transformation of Pfizer into a digital powerhouse that will generate patient superior experiences which results in better health outcomes.

The Analytics Experience team, which is part of the Analytics & Data org within Digital Health, Medicines, and Artificial Intelligence, is responsible for the creating a seamless experience for analytics experts to harness the potential of big data, machine learning, and interactive analytics through a unified platform across the enterprise – from scientific/clinical to commercial across all Pfizer geographies.

Part of the Analytics Experience team is a User Success team that will be responsible for platform adoption: onboarding, enabling, and supporting self-sufficient analytical users from across the Pfizer business as part of the enterprise analytics platform, Pfizer Insights. Pfizer Insights will be the digital engine that brings together investments we have made into a unified experience for colleagues that take us to the next level of value creation. It powers next generation insights by developing enterprise-grade data foundations, allowing data to flow horizontally, enabling a versatile analytics environment, and embedding insights into day-to-day work to create a digital, data-driven culture.

This role provides technical enablement and will partner with key groups from Worldwide Research and Development (WRD), Digital Analytics and Data, and external vendors to ensure that participating analysts and data scientists in WRD have everything they need to conduct analytics effectively and efficiently for their user cases. The candidate will need to have data science experience to work on proof-of-concept use cases in partnership with WRD analytics experts which will include understand data needs and concepts, developing AI and ML models, and creating visualizations. Fast onboarding, ongoing support, training, and robust change-management is critical to their success. You will have the ability to diagnose issues, solve issues independently where possible, and/or connect analysts with a comprehensive team of experts to provide the most appropriate support to meet their needs and see that they meet their goals.

ROLE RESPONSIBILITIES

• With supervision, you will:

• Work with the business partner to establish relationships with customers and understands data science needs

• Develop documentation including initial requirements and design for data and AI/ML use cases.

• Create data pipelines for efficient and repeatable data wrangling, preprocessing, and feature engineering

• Apply statistical analysis and visualization techniques to various data (E.g., principal components analysis)

• Apply various ML and advanced analytics techniques to perform classification or prediction tasks

• Testing of ML models, such as cross-validation, A/B testing, bias, and drifts

• Build WRD domain knowledge over time

• Actively support the enablement of users via:

• Contributing and managing our knowledge base and community forums

• Partnering to offer short term project/solutions support and guidance

• Coordinate and promote training offerings

• Technical Support Liaison

• Up-skill to and maintain ‘expert’ status in our data science platform

BASICQUALIFICATIONS

• BS in computer science, data science, /or an engineering/quantitative field. 

• At least 3 years of experience in field of data and analytics

• Hands-on skills in data engineering, machine learning and/or data visualization skills

• Experience with writing SQL queries on relational databases

• Experience with coding with Python for data analysis, data visualization, and machine learning modeling

• Strong communication skills (written & verbal)

• Experience with analytical problem solving

PREFERRED QUALIFICATIONS

• Project management experience 

• A passion for problem-solving, comfort with ambiguity, and creativity 

• Ability to thrive in a dynamic and fast-paced environment and drive change, and collaborate effectively with a variety of individuals and organization 

• Strong hands-on skills for data and machine learning pipeline orchestration via Dataiku (DSS 9 or 10), or similar, platform

• Strong hands-on skills in Data Visualization platforms (e.g. Tableau, Spotfire)

• Containerization and underlying infrastructure knowledge to support performance and resource optimization is a plus

• Pharma & Life Science research and development functional knowledge is a plus 

• Pharma & Life Science research and development data literacy is a plus 

LI#PFE

PHYSICAL/MENTAL REQUIREMENTS

None

None

 
Work Location Assignment: Flexible