Associate Data Scientist

Role Summary

Associate Data Scientist at Pfizer: responsible to assist Data Management staff to leverage data assets to deliver business insights, implement automation and AI methods, collaborating with cross-functional teams to enhance tactical and strategic decision making.

Responsibilities

• Assist the manager implement global strategies, initiatives, processes, and standards to ensure consistent, efficient, and quality Data Science processes to meet expected quality, timelines and deliverables.
• Run SQL queries to extract operational, clinical data and specifications from various information systems.
• Independently assess and analyze data quality, understand business processes and how they impact data quality, prepare data including labeling of data for machine learning experiments.
• Pilot and build POC’s to demonstrate and test business value of machine learning models, understand model metrics, iteratively improve model performance with tech leads and vendors.
• Analyze, interpret, and summarize machine learning model results.
• Operationalize and maintain the models.
• Develop presentations and trainings for business users to increase understanding of AI, data science and automation within Data Management.

Qualifications

• Bachelor’s degree or above or equivalent experience in a scientific or business-related discipline required; degree in informatics, computer science, statistics, or related field preferred.
• Works independently, handles unusual situations with minimal instruction; able to organize tasks, time, and priorities; multi-tasking ability.
• Ability to communicate with internal and external stakeholders, locally and globally.
• At least 1–2 years of experience with clinical data, SQL, and analytics.

Preferred Qualifications

• Experience with Python and/or R, SAS and machine learning model implementation.
• SQL experience with relational databases such as PostgreSQL, Oracle, or Microsoft SQL Server.

Additional Requirements

• Non-standard work hours to cover global meetings or travel.
• Work Location: Hybrid (live within commuting distance and work on-site ~2.5 days per week).