Data Scientist Ii, Predictive Scientific Engagement

**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 rich in diversity. Take your career farther than you thought possible.

BMS Hyderabad is an integrated global hub where our work is focused on helping patients prevail over serious diseases by building sustainable and innovative solutions. This important science, technology, and innovation center will support a range of technology and drug development activities that will help us usher in the next wave of innovation.

***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
- 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) to solve complex business challenges
- Collaborate with data engineers and IT teams to ensure data availability, quality, and reliability for analysis and modeling
- Communicate complex analytical findings and insights to both technical and non-technical stakeholders through clear and compelling visualizations, reports and presentations
- Stay up-to-date with the latest methodologies and best practices in statistical analysis, machine learning, and the biopharma industry
- Mentor and provide guidance to junior data scientists and actively participate in knowledge sharing and team development initiatives

***Skills and competencies**
- Experience with building and deploying data science and data engineering solutions using established industry methods (MLOps, Git) to pharmaceutical related datasets is preferred
- Proficiency in programming languages such as Python or R for data manipulation, analysis and modeling
- Familiarity with data visualization tools such as Tableau, Power BI or matplotlib/seaborn for effective communication of findings
- Strong understanding of experimental design, hypothesis testing and A/B testing methodologies
- Excellent problem-solving skills and the ability to think critically and creatively to tackle complex business challenges
- Excellent communication and presentation skills to convey complex concepts to technical and non-technical stakeholders
- Experience with cloud platforms (e.g., AWS, Azure) and big data technologies (e.g., Hadoop, Spark) is a plus
- Strong organizational and time management skills, with the ability to prioritize tasks and meet deadlines in a fast-paced environment

Experience:

- We welcome a bachelor’s, master's or Ph.D. degree in a relevant field such as Data Science, Statistics, Computer Science or a related discipline.
- Proven experience (typically 2 to 5 years) in a data science role, preferably within the biopharma or pharmaceutical industry
- 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, NoSQL or similar technologies
- Demonstrated ability to develop and implement predictive models and machine learning algorithms
- Experience working with healthcare data, clinical trials, or related domains is highly desirable
- Solid understanding of the biopharma industry, including regulatory requirements and healthcare data sources
- Familiarity with sourcing social media data from external sources.

GBOHYD #LI-Hybrid

**Uniquely Interesting Work, Life-changing Careers**

**On-site Protocol**

BMS has a diverse occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role:
Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design ro