General Coop LDO Data Science - Spring 2023
At Bristol Myers Squibb, we are inspired by a single vision – transforming patients’ lives through science. In oncology, hematology, immunology and cardiovascular disease – and one of the most diverse and promising pipelines in the industry – each of our passionate colleagues contribute to innovations that drive meaningful change. We bring a human touch to every treatment we pioneer. Join us and make a difference.
Leads discovery and optimization (LDO) is a diverse group of scientists and engineers, providing critical assay information to therapeutic research centers (TRCs) throughout research and early development (R&ED). We are seeking a highly motivated and innovative student to join the data science and advanced analytics team within LDO, for a 6 month co-op starting January 2023. Team objectives include the development of machine learning, data science models and analytical tools to improve operational efficiencies, increase the impact of data packages, and improve data analysis capabilities.
We invite undergraduates with appropriate training from all backgrounds to apply for this co-op in our fun and fast-paced data science team. You will work in a highly dynamic environment at the center of the R&ED drug discovery engine to use cutting edge machine learning tools applied to complex drug discovery problems. You will be assigned a project which integrates with the data science team’s objectives and core mission to influence faster and more robust drug candidate decision making. Importantly, this opportunity will expose you to a myriad of real-world examples and datasets that will serve to hone and advance your data science skillsets to the next level!
- Develop cutting edge data science and machine learning scripts/tools to guide in-depth data analyses via collaborations with LDO bench scientists, the data science team, and external partners
- Present analyses and tools in technical and non-technical forums
- Produce high quality output within the specified timelines for competing priorities
Qualifications & Experience
- Junior or Senior undergraduate enrolled in a technically relevant degree program, such as Engineering, Computer Science, Mathematics, Chemistry, etc.
- Programming experience in one or more scripting languages such as Python or R
- Experience with advanced machine learning concepts such as Bayesian optimization, feature engineering, etc
Around the world, we are passionate about making an impact on the lives of patients with serious diseases. Empowered to apply our individual talents and diverse perspectives in an inclusive culture, our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.
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.
Physical presence at the BMS worksite or physical presence in the field is an essential job function of this role which the Company deems critical to collaboration, innovation, productivity, employee well-being and engagement, and enhances the Company culture.
To protect the safety of our workforce, customers, patients and communities, the policy of the Company requires all employees and workers in the U.S. and Puerto Rico to be fully vaccinated against COVID-19, unless they have received an exception based on an approved request for a medical or religious reasonable accommodation. Therefore, all BMS applicants seeking a role located in the U.S. and Puerto Rico must confirm that they have already received or are willing to receive the full COVID-19 vaccination by their start date as a qualification of the role and condition of employment. This requirement is subject to state and local law restrictions and may not be applicable to employees working in certain jurisdictions such as Montana. This requirement is also subject to discussions with collective bargaining representatives in the U.S.
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