Data Analyst with Pharma Domain

Job Description

Product Development (PD) at Bristol Myers Squibb is committed to accelerating CMC development to launch through strategic investments in novel development and manufacturing platforms, new development playbooks, and advancing innovation though modeling, AI/ML, and automation. These specific strategic investments are known as our Development Excellence strategy. As part of this organization, the Product Development Strategy group is accountable for developing a holistic digital and modeling strategy and its global integration and implementation. 

We are seeking a highly motivated scientist to join the Modeling and Digital Strategy group as a data integrator. In this role, the data integrator will be responsible for collecting and curating data for use in predictive models across a range of use cases focusing on accelerating process development. The role will participate in highly visible and agile cross functional teams with scope spanning the digital and modeling space. They will collaborate closely with partners within PD such as drug substance, drug product and analytical functions as well as with business partners such as IT. This role will report to the Sr Director, Product Development Strategy. 

Qualifications

Bachelor's degree or higher in a relevant field such as chemical engineering, life sciences, data science, or computer

science

At least 2 years of experience in process development or data analysis in the pharmaceutical industry or a related

domain

Familiar with data standards, ontologies, and metadata for pharmaceutical process development data

Excellent communication and interpersonal skills to work effectively with diverse stakeholders

Strong problem-solving and analytical skills to handle complex and large-scale data challenges

Responsibilities

Self-motivated and proactive to learn new skills and technologies

Collect and curate data from multiple sources including electronic notebooks, spreadsheets, slide decks, and

instrument files

Ensure data quality, consistency, and completeness across different data sets

Apply data standards, ontologies, and metadata to facilitate data integration and analysis

Support data discovery, access, and sharing across the organization

Collaborate with scientists and engineers to identify data sources and locations, understand data requirements and

challenges, and provide data solutions