Bristol Myers Squibb
Biopharma
DataScientistII
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Data Scientist II at Bristol Myers Squibb. Skills: Data Science, Machine Learning, Predictive Modelling, AI/GenAI. Ideate advanced solutions. Design advanced solutions”
What You'll Achieve.
Drive actionable recommendations
Industry & Context.
Problem-solving; Critical thinking; Creative thinking; Root cause analysis
What They're Looking For.
Must Have
Bachelor's, Master's or Ph.D. degree, 2 to 5 years experience in data science, SQL proficiency, Statistical analysis, Machine learning, Predictive modelling techniques
Nice to Have
Ph.D. degree, Experience in biopharma or pharmaceutical industry, Experience with healthcare data, Experience with clinical trials, Familiarity with sourcing social media data, Exposure to AI/GenAI technologies, Experience with MLOps, Experience with Git, Experience with cloud platforms, Experience with big data technologies, Experience with version control tools
What You'll Do.
Ideate advanced solutions
Design advanced solutions
Develop advanced solutions
Model advanced solutions
Deploy advanced solutions
Collaborate with stakeholders
Define project objectives
Formulate data-driven hypotheses
Identify KPIs for analysis
Gather structured data
Gather unstructured data
Pre-process structured data
Pre-process unstructured data
Explore structured data
Explore unstructured data
Apply statistical analysis
Apply machine learning algorithms
Apply predictive modelling techniques
Drive actionable recommendations
Conduct exploratory data analysis
Identify patterns in data
Identify anomalies in data
Propose solutions to business problems
Develop predictive models
Implement predictive models
Develop AI/GenAI solutions
Solve complex business challenges
Collaborate with data engineers
Collaborate with IT teams
Ensure data availability
Ensure data reliability
Communicate analytical findings
Stay up-to-date with methodologies
Stay up-to-date with best practices
Mentor junior data scientists
Provide guidance to junior data scientists
Participate in knowledge sharing
Participate in team development
How You'll Work.
Team & Collaboration
Technical stakeholders; Non-technical stakeholders; Data engineers; IT teams
Communication Scope
Presentations; Visualizations; Reports
Full Job Description
**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](https://careers.bms.com/working-with-us). **_Roles & Responsibilities_** •Hands-on data scientist or machine learning engineer that will be expected to ideate, design, develop, model and deploy advanced solutions •Collaborate with stakeholders to define project objectives, formulate data-driven hypotheses and identify KPIs for analysis •Gather, pre-process and explore large-scale structured and unstructured data from diverse sources, including clinical trials, patient records and genetic data •Apply advanced statistical analysis, machine learning algorithms and predictive modelling techniques to extract insights and develop models that drive actionable recommendations •Conduct exploratory data analysis (EDA) to identify patterns and anomalies in the data and propose solutions to business problems •Develop and implement predictive models (e.g., regression, clustering, time series forecasting) as well as AI/GenAI solutions to solve complex business challenges •Collaborate with data engineers and IT teams to ensure data availability, quality, and reliability for analy
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