Data Scientist II, Development Operations

1 month ago

hyderabad, India Bristol Myers Squibb Full time

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.

Data Scientist II, Development Operations

Summary : We are seeking an experienced individual to join an exceptional team that creates advanced analytical solutions to support Development Operation at Bristol Myers Squibb. This position will provide hands-on data science and machine learning engineering support and leadership for an end-to-end ecosystem of solutions for in-line / pipeline, short- / long-term. Specifically, this role will code, validate and test machine learning and/or simulation models, and develop analytics apps to allow users to interact with these models.

Roles & Responsibilities:

Conduct analysis and interpretation of complex data sets to derive meaningful insights and recommendations that enhance drug development process Develop robust and scalable machine learning (ML) or simulation models. Extract insights from epidemiology, real world data, market research and other sources to support drug development and clinical trial forecasting models. Stay informed about advancements in pharma forecasting methodologies and tools. Continuously monitor and evaluate the performance of forecasting models, including validation of ML models. Prepare reports, dashboards and presentations to communicate findings, insights and recommendations to stakeholders Collaborate with US & Hyderabad based Business Insights & Analytics partners to identify business problems and create/conduct analytic plans to address those questions Support opportunities to enhance the business impact of predictive models, such as performance, quality and efficiency. Work across matrix teams to develop and enhance data infrastructure, data pipelines and analytical tools for efficient data collection, processing and analysis Document solution specifications (e.g., architecture, data flows, algorithms) to ensure transparency / reproducibility.

Skills & Competencies:

Strong analytical thinking and problem-solving skills with the ability to analyze complex data sets and draw meaningful conclusions Proficiency in statistical analysis machine learning, and data modeling Advanced NLP techniques and deep learning methodologies Strong communication skills with the ability to present complex information to non-technical stakeholders in a clear manner Strong business acumen and strategic thinking, with the ability to translate analytical findings into actionable insights and recommendations.

Experience:

Bachelor's or master's degree in Computer Science, Engineering, Applied Math, Bio Informatics, Operations Research or equivalent working experience in a highly analytical field 3+ years experience in a similar data science role, preferably within the biopharma or pharmaceutical industry. Effective communication and collaboration skills Demonstrated ability to manage multiple projects simultaneously and deliver high-quality results within specified deadlines Preferably, experience advanced analytics techniques such as imputation, ML engineering, hyper parameter tuning, MLOPs as well as off-the-shelf solutions Experience in data processing and visualization tools, and statistical software packages (e.g., SQL, R, Python, Tableau) Deep interest in the drug development process, and preferably, experience with pharmaceutical industry analytics including data sources, market research, R&D data, or real-world data

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