Data Scientist/ Data Engineer

Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.

Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us.

Position Summary:

At BMS, digital innovation and Information Technology are central to our vision of transforming patients’ lives through science. To accelerate our ability to serve patients around the world, we must unleash the power of technology. We are committed to being at the forefront of transforming the way medicine is made and delivered by harnessing the power of computer and data science, artificial intelligence, and other technologies to promote scientific discovery, faster decision making, and enhanced patient care. If you want an exciting and rewarding career that is meaningful, consider joining our diverse team!

As the Data Scientist for the Clinical Data Ecosystem within Global Drug Development (GDD) IT at BMS, you will be part of the Drug Development IT team delivering platform, data, and analytics solutions for Global Biostatistics and Data Sciences, Clinical Data Management, and related domains such as Clinical Analytics, Site Selection, Feasibility, and Real-World Evidence.

Key Responsibilities:

• Collaborate with Global Drug Development (GDD), Global Biometric & Data Science (GBDS) & Enterprise Data and Analytics Platform team organizations, to understand business needs, influence, shape and adopt data and technology strategy.

• Hands-on Development Data Scientist Analyst that will be expected to ideate, design, develop, model and deploy advanced solutions

• Conduct analysis and interpretation of complex data sets to derive meaningful insights and recommendations based on an understanding of Drug Development priorities, critical issues, and value levers

• Agile problem-solving ability and desire to learn new things and continuously improve.

• Gather, pre-process and explore large-scale structured and unstructured data from diverse sources.

• Apply advanced statistical analysis, machine learning algorithms and predictive modelling techniques to extract insights and develop models that drive actionable recommendations

• Conduct exploration data analysis (EDA) to identify patterns and anomalies in the data and propose solutions to business problems

• Ability to simplify complex technical and scientific concepts for non-technical stakeholders.

• Prior experience working in an Agile methodologies/Product based environment.

Qualifications & Experience:

• Bachelor’s degree in computer science, Information Technology, Life Sciences, or a related field. Advanced degree preferred.

• Proven experience (typically 4+ years) in a data and analytics role, including direct development experience.

• Experience working with large datasets, data visualization tools, statistical software packages and platforms (specifically React, Python, advanced SQL, Domino, AWS, GitHub)

• Strong background in statistical analysis, machine learning, and predictive modelling techniques

• Experience in handling and analyzing large-scale structured and unstructured data sets using SQL or similar technologies

• Experience with building and deploying data science and data engineering solutions using established industry methods (MLOps,Git) to Complex datasets is preferred

• Demonstrated ability to develop and implement predictive models and machine learning algorithms

• Experience working with complex datasets is highly desirable

• Experience with cloud storage and compute infrastructure (e.g., AWS, Azure) and knowledge of automation and monitoring tools.

• Demonstrates a focus on improving processes, structures, and knowledge within th