Vice President, Data Scientist

Job Description

Position Summary: The Vice President, Data Scientist plays a critical role in driving data-driven decision-making within BNY by leveraging advanced data analytics and statistical modeling. This position is situated within the Data Science job family, focusing on the tech-driven function of Data Management. The individual will contribute to BNY's strategic pillars by enhancing operational efficiency and innovation through robust data insights. This role aligns with BNY's principles by fostering a culture of excellence, collaboration, and client-focused solutions, ensuring that data-driven strategies propel business growth and client satisfaction.

Primary Responsibilities:

• Lead complex data analysis projects by applying advanced statistical techniques and machine learning models to extract actionable insights, driving business strategy and operational improvements.
• Collaborate with cross-functional teams to design and implement data-driven solutions that align with organizational goals, demonstrating expertise in data science methodologies.
• Manage and refine large datasets, ensuring data integrity and accuracy by utilizing best practices in data management and governance.
• Develop and maintain predictive models that forecast business trends, providing strategic recommendations supported by data evidence.
• Stay updated on industry trends and emerging technologies in data science to continuously enhance analytical capabilities and methodologies.
• Communicate findings and insights effectively to stakeholders at all levels, translating complex data concepts into clear and actionable business strategies.

Education/Qualifications:

• Bachelor's degree in Data Science, Computer Science, Statistics, or a related field or the equivalent combination of education and experience required.
• Advanced degree preferred.

Experience:

• Typically 3-6 years of experience

Skills:

• Proficiency in statistical programming languages such as Python, R, or SQL.
• Strong analytical and problem-solving skills, with the ability to interpret complex datasets and generate actionable insights.
• Excellent communication skills, capable of conveying data-driven insights to both technical and non-technical audiences.