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    Data Scientist - Chicago, United States - Calamos Asset Management

    Calamos Asset Management
    Calamos Asset Management Chicago, United States

    1 week ago

    Default job background
    Description
    Calamos Advisors LLC has an opening for Data Scientist in Naperville, Illinois.

    Responsible for acquiring the necessary data, running various modelling and other analytical techniques to draw insights, and preparing the results in a way that is conducive to business decision making.

    Responsible for running advanced statistical analyses identifying trends and exploring opportunities with the aim of generating actionable insights. Develop predictive models that address business needs and measure performance of these models to ensure business improvements. Design, develop and implement product prototypes that are piloted and converted to products for use within the business.

    Work closely with the business to collect feedback, incorporating in the product, as well as maintaining and improving its functionality over time.

    Develop and institutionalize best practices for scalable data processing and machine learning. Assess and mitigate possible risks and support and perform product and application upgrades to address them.

    Work closely with data management (IT) colleagues to guide them on structuring relevant data to facilitate data exploration and fast prototyping.

    Work closely with business insight managers to ensure business relevance of analytics processes and products. Telecommuting permitted one day per week.
    Job Requirements

    Position requires a Master's degree in Data Science, Industrial Engineering, Econometrics, Math, Physics, or related and six months of related work experience.


    Must also have work or academic experience in:
    Machine learning;
    Applying statistical concepts including distribution functions, probability, and Bayes' Theorem;
    Addressing critical business problems by developing and testing various machine learning models including, but not limited to, tree-based models, unsupervised clustering models, and deep learning architectures; and
    Using programming languages, Python, SQL, or Spark, in a Databricks environment to maximize coding efficiency.

    #J-18808-Ljbffr
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