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    Senior Data Scientist with Banking Domain - Boston, United States - New York Technology Partners

    New York Technology Partners
    New York Technology Partners Boston, United States

    1 month ago

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    Accounting / Finance
    Description

    Title: Senior Data Scientist with Banking Domain

    Location: Boston, MA (Onsite)

    Duration: 6 months contract

    Job Description

    We are seeking an experienced and highly skilled Data Scientist to lead the development and implementation of advanced data modeling and predictive analytics to support investment strategies.

    The ideal candidate should have extensive experience in data science designing and deploying statistical modelling with at least 6 years of hands-on experience in Financial/Investment / Asset Management / Fixed Income.

    Job Responsibilities

    Utilize data analytics and advanced statistical techniques to inform investment decision-making and drive business growth.

    Collaborate with cross-functional teams to identify opportunities for leveraging data to enhance investment strategies.

    Develop and maintain a robust data infrastructure to support data-driven decision-making.

    Stay updated on industry trends and best practices in data science and investments, and implement new techniques and tools as needed.

    Lead the development and implementation of advanced data modeling and predictive analytics to support investment strategies.

    Provide strategic guidance and recommendations to senior leadership on investment opportunities and risks based on data analysis.

    Oversee the creation and maintenance of data dashboards and reports to track investment performance and identify areas for improvement.

    Collaborate with other departments to ensure alignment and integration of data-driven strategies across the organization.

    Mandatory Skills

    Primary Skills : Has experience with data science, statistical modeling and time series analysis of financial markets data, Fixed Income Assets, Investment Banking.

    Secondary Skills : Has experience in Gen AI , Language Model etc.

    Required Education

    Bachelor's degree in computer science or a related field.

    Competencies typically acquired through an advanced degree (in Statistics, Mathematics, Data Science or other relevant field of study)

    Proficiency in the mathematics underlying Machine Learning

    Ability to present complex technical information in a clear and concise manner to a variety of audiences.

    Required Experience

    Minimum 14+ years of experience in data science designing and deploying statistical modelling with at least 6 years of hands-on experience in Financial/Investment / Asset Management / Fixed Income.

    Has experience with data science, statistical modeling and time series analysis of financial markets data, Fixed Income Assets and/or Investment Banking.

    Has experience in Gen AI , Language Model etc.

    Worked for asset management firms in roles aligned to the front office.

    Has advanced knowledge of python and/or R

    Asset Allocation, Research, quat engineering

    Broad experience with hands-on modelling and DS lifecycle activities, particularly in Python, and ability to communicate at a high level with DS and non-technical leaders

    Knowledge of graphical packages such as plotly or gg plot

    Excellent understanding of Statistical modeling, Machine Learning (Supervised, Unsupervised, Recommendation engines, Optimization etc.) Deep Learning (RNN, CNN, LSTM, Auto encoders, GANS etc.), Natural Language Processing techniques and algorithms

    Strong coding experience in Python, Pyspark, Keras/tensorflow

    Experience with SQL & at least one NoSQL databases

    Experience of working on any of cloud platform (AWS, Azure, IBM etc.)

    Work closely with data engineers to source, analyze and engineer features, collaborate with fellow data scientists to develop, test and deploy Machine Learning models

    Exposure to creation of data pipelines to engineer apps deployment (CI/CD) across platforms and environments and working with ML pipelines

    Demonstrate analytical and problem-solving skills, particularly those that apply to the big data environment


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