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    Bank of America:Quantitative Finance Analyst - Jersey City, United States - Hitalent

    Hitalent
    Hitalent Jersey City, United States

    1 week ago

    Default job background
    Description
    Develop, implement and maintain statistical models, machine learning algorithms, analytical libraries, and tools to support Risk Management functions.

    Apply software engineering (Agile), object-oriented design and programming (Python, R & C++) skills to develop high-performance, scalable, and reusable software solutions.

    Develop and maintain the bank's in-house statistical and AI/ML libraries to support model development efforts, including but not limited to Regression, XGBoost, Random Forests, Clustering and NLP/NLU for large-scale distributed systems (Spark/PySpark, Hadoop/HDFS, HIVE).

    Develop and implement cross-platform (Oracle, Teradata, etc.) queries to obtain business/risk metrics.
    Communicate quantitative topics to both technical and non-technical audiences to both client groups and fellow developers.

    Develop and test machine learning/AI development models & algorithms, including SVM, Clustering, Random Forest, XGBoost, NLP/NLU, and Pattern Recognition to identify and classify quantitative patterns.

    Implement advanced high-performance Python code for large-scale distributed computing environments such as Apache Spark, Hadoop/HIVE to develop scalable, reusable analytical and quantitative models.

    Create in-house data mining, data processing and data analysis and visualization tools using Python and Tableau to gain business insight from the data.

    Use JIRA to track projects, tasks and deadlines in the context of software development.

    REQUIRED SKILLS & EXPERIENCE :
    Master's degree or equivalent in Engineering (any), Statistics, Mathematics, or related; and
    2 years of experience in the job offered or a related quantitative occupation.
    Must include 2 years of experience in each of the following:
    Developing and testing machine learning/AI development models & algorithms, including SVM, Clustering, Random Forest, XGBoost, NLP/NLU, and Pattern Recognition to identify and classify quantitative patterns;
    Implementing advanced high-performance Python code for large-scale distributed computing environments such as Apache Spark, Hadoop/HIVE to develop scalable, reusable analytical and quantitative models;
    Creating in-house data mining, data processing and data analytical and visualization tools using Python and Tableau to gain business insight from the data; and,
    Using JIRA to track projects tasks and deadlines in the context of software development.
    The employer will accept pre or post-Master's degree experience.
    10% domestic or international travel, as required.

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