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seekers for CCB Risk - Machine Learning Risk Modeling - Associate

1.00 to 4.00 Years   Mumbai City   16 Aug, 2022
JPMorgan
Job LocationMumbai City
EducationNot Mentioned
SalaryNot Disclosed
IndustryBanking / Financial Services
Functional AreaGeneral / Other SoftwareSales / BD
EmploymentTypeFull-time

Job Description

    CCB Risk Modeling team is searching for talents to develop and implement machine learning models/ statistical models/ segmentations/strategies, possibly leveraging big data and distributed computing platforms, with applications in risk management for its consumer and small business portfolio. The successful candidate will drive long term profitable growth with strong business acumen, collaborate in a team environment, and effectively communicate results to senior management.CCB Risk Modeling Applied AI/ML Associate
    • Utilize cutting-edge approaches to design and develop sophisticated machine learning models to drive impactful decisions for the business
    • Leverage big data/distributed computing/cloud computing platforms to optimize and accelerate model development processes
    • Work closely with the senior management team to develop ambitious, innovative modeling solutions and deliver them into production
    • Collaborate with various partners in marketing, risk, technology, model governance, etc. throughout the entire modeling lifecycle (development, review, deployment, and use of the models)
    Basic Qualifications
    • Ph.D. or MS degree in Mathematics, Statistics, Computer Science, Operational Research, Econometrics, Physics, or other related quantitative fields
    • Deep understanding of advanced machine learning algorithms (e.g., regressions, XGBoost, Deep Neural Network CNN and RNN, Clustering, Recommendation) as well as design and tuning
    • Polished and clear communication
    Preferred Qualifications
    • 3+ years of experience in developing and managing predictive risk models in financial industry
    • Demonstrated experience in designing, building, and deploying production quality machine learning models such as XGBoost, GBM, etc. Experience in interpreting deep learning models is a plus
    • At least one year of experience and proficiency in coding (e.g., Python, Tensorflow, Spark, or Scala) and big data technologies (e.g., Hadoop, Teradata, AWS cloud, Hive)
    • Demonstrated expertise in data wrangling and model building on a distributed Spark computation environment (with stability, scalability and efficiency). GPU experience is desired
    Strong ownership and execution; proven experience in implementing models in production,

Keyskills :
source system analysisstrong business acumenbig datarisk modelsdeep learningrisk modelingdata wranglingsmall business

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