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    Data Scientist - Bangalore, India - Danaher

    Danaher
    Danaher background
    Full time
    Description

    Beckman Coulter Life Sciences' mission is to empower those seeking answers to life's most important scientific and healthcare questions. With a legacy spanning 80+ years, we have long been a trusted partner to our customers, who are working to transform science and healthcare with the next groundbreaking discovery. As part of our team of more than 2,900 associates across 130 countries, you'll help drive our vision of accelerating answers—and our commitment to excellence.

    Beckman Coulter Life Sciences is one of 10 Life Sciences companies of Danaher. Together, we accelerate the discovery, development and delivery of solutions that safeguard and improve human health.

    Do you want to work in Industry 4.0 & Lab of the future in order to improve performance and quality as well as reducing our environmental footprint? Do you enjoy AI, Operations Research Algorithms? Then read on

    We are currently seeking a Data Scientist focused on Operations Research who will be responsible for leading and owning digital innovations end-to-end.

    In this role, you will be responsible for:

    • Understanding the business problems our Operations teams are facing.
    • Identifying digital and advanced solutions to resolve our problems and select the one you find the most relevant.
    • Driving the technical projects from end to end, developing algorithms, working on their operational implementations.

    The required qualifications for the job include:

    • MS with 3+ year experience, or PhD in any of the following fields (or similar): Mathematical Engineering or Industrial Engineering, Computer Science, System engineering with focus on operations research, statistics, mathematics.
    • Proven track record in Operations Research, such as large-scale optimization problems, graph (network), MIP, MINLP or stochastic optimization; discrete events and continuous simulation; probability, statistics, and statistical modelling techniques
    • Experience and willingness to own problems end-to-end. Be willing to get full stack implication to deliver high-quality data-driven applications to ensure both your team and our customers success.
    • Experience in using OR-tools and numerical solvers such as GLPK, IpOpt, Cplex
    • Very good knowledge of Python & its data science libraries such as Pandas, Numpy, Scikit, TensorFlow, PyTorch

    It would be a plus if you also possess previous experience in:

    • Experience or knowledge in data modeling and ML, Deep Learning
    • Experience in Healthcare and LifeScience Industry
    • Knowledge of SQL, C# or Java

    Hybrid Job Posting Language:

    At Beckman Coulter Life Sciences we believe in designing a better, more sustainable workforce. We recognize the benefits of flexible, hybrid working arrangements for eligible roles and are committed to providing enriching careers, no matter the work arrangement. This position is eligible for a hybrid work arrangement in which you can work part-time at the Company location identified above and part-time remotely from your home. Additional information about this hybrid work arrangement will be provided by your interview team. Explore the flexibility and challenge that working for Beckman Coulter Life Sciences can provide.

    At Danaher we bring together science, technology and operational capabilities to accelerate the real-life impact of tomorrow's science and technology. We partner with customers across the globe to help them solve their most complex challenges, architecting solutions that bring the power of science to life. Our global teams are pioneering what's next across Life Sciences, Diagnostics, Biotechnology and beyond. For more information, visit

    At Danaher, we value diversity and the existence of similarities and differences, both visible and not, found in our workforce, workplace and throughout the markets we serve. Our associates, customers and shareholders contribute unique and different perspectives as a result of these diverse attributes.


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