Senior Data Scientist - Johannesburg - Boardroom Appointments

    Boardroom Appointments
    Boardroom Appointments Johannesburg

    1 week ago

    Boardroom Appointments background
    Description

    Job Description:

    We are seeking an experienced Data Scientist to join our team at {company}. The ideal candidate will have a strong background in manipulating data sets and building statistical models, with a minimum of 5-7 years of experience.

    The successful candidate will possess a degree in a quantitative field such as Mathematics, Computer Science, or another relevant field. Strong problem-solving skills, with an emphasis on product development, are essential for this role.

    Excellent written and verbal communication skills are required for coordinating across teams, and the ability to implement ML systems using TensorFlow and PyTorch is a must.

    The following skills are highly desirable:

    • Mastery of statistical computer languages (R, Python, SQL, etc.) for data manipulation and insight drawing.
    • Experience querying databases/datasets.
    • Familiarity with statistical and data mining techniques, including GLM/Regression, Random Forest, Boosting, Trees, text mining, social network analysis, etc.
    • Able to create and use advanced machine learning algorithms and statistics, including regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc.
    • Knowledge of various machine learning techniques and their real-world advantages/drawbacks.
    • Advanced statistical techniques and concepts, including properties of distributions, statistical tests, and proper usage.

    Responsibilities:

    The successful candidate will be responsible for:

    • Working with stakeholders throughout the organization to identify opportunities for leveraging company data to drive business solutions.
    • Mining and analyzing data from company databases to drive optimization and improvement of product development, marketing techniques, and business strategies.
    • Assessing the effectiveness and accuracy of new data sources and data gathering techniques.
    • Developing custom data models and algorithms to apply to data sets.
    • Using predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting, and other business outcomes.
    • Developing a company A/B testing framework and testing model quality.
    • Coordinating with different functional teams to implement models and monitor outcomes.
    • Developing processes and tools to monitor and analyze model performance and data accuracy.
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