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Data Scientist III, Revenue Forecasting
4 months ago
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 III, Revenue Forecasting
Summary : We are seeking an experienced Data Scientist to join an exceptional team that creates advanced analytical solutions to support revenue forecasting at Bristol Myers Squibb. This position will provide hands-on data science and machine learning engineering support for an end-to-end ecosystem of solutions for in-line / pipeline, short- / long-term forecasts. Specifically, this role will code, validate and test machine learning and/or simulation models, and develop apps to allow users to interact with these models. They will report to a HYD-based Sr. Manager for Data Science, in close collaboration with the US-based team.
Roles and responsibilities:
Develop robust and scalable machine learning (ML) or simulation models. Model factors like epidemiology, patient flow, competition, and others impacting drug development/commercialization. Analyze forecast input data (incl. sales, epidemiology, competition) to assess quality and pre-processing needs. Develop ML models to support aggregation of forecasting assumptions while accounting for uncertainty. Extract insights from epidemiology, real world data, market research and other sources to support patient simulations. Stay informed about advancements in pharma forecasting methodologies and tools. Continuously monitor and evaluate the performance of forecasting models, including validation of ML models. Engage key stakeholders to understand their needs and translate them into technical specifications. Align closely with the US-based team and project leaders on priorities, project planning and management. Work closely with data scientists and domain experts to ensure compatibility of forecasting solutions with other tools. Work with IT as needed on data management and infrastructure related to forecasting solutions. Support the deployment of forecasting solutions, striving for seamless integration with existing systems. Develop UI apps to allow stakeholders to effectively interact with new forecasting solutions. Support opportunities to enhance the business impact of forecasting models, such as quality and efficiency. Document solution specifications (e.g., architecture, data flows, algorithms) to ensure transparency / reproducibility.Skills & competencies:
Statistical analysis, machine learning, and data modeling Programming languages such Python, R, or similar Data manipulation, analysis, and querying using SQL or similar Excellent problem-solving and analytical skills, with the ability to weigh tradeoffs in solution development such as cost, time, quality and risk.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 5+ years experience working as a Data Scientist or similar role, preferably focusing on pharma revenue forecasting, incl. hands-on coding in Python, R, SQL Effective communication and collaboration skills Demonstrated ability to manage multiple projects simultaneously and deliver high-quality results within specified deadlines Preferably, experience with pharma forecasting techniques such as demand vs epi-based forecasts, baselining, event modeling, time series analysis and simulation, as well as off-the-shelf forecasting platforms Deep interest in the drug development and commercialization process, and preferably, experience with pharmaceutical industry analytics including data sources, market research, sales data, or real-world data#GBOHYD
