Bristol Myers Squibb

Biopharma

DataScientistII

₹22–35L ~AI est. India FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid+ candidates.

The Brief

“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.

Biopharma
Problems you'll solve

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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