Chief Data Office-Data Analytics VP

Bank of ChinaNew York, NY
$110,000 - $230,000

About The Position

The Data Analytics VP will serve as a key member of the CDO Data Analytics team, supporting bank‑wide data and business analytics initiatives and driving improved business outcomes through the effective use of data across the organization.

Requirements

  • Bachelor’s degree required
  • At least 5 years of experience in data analytics, SQL, Python and Business Intelligence Tools
  • At least 3 years of experience in dashboard development
  • At least 2 years of experience in Machine Learning/AI
  • Good communication skills (written and verbal) and project management experience required
  • Financial Services Experience Required
  • Strong analytical, machine learning and Artificial Intelligence (AI), decision-making and problem-solving skills

Nice To Haves

  • Master's degree in computer science/statistics/applied analytics/business analytics or other analytics relevant majors preferred
  • Banking experience preferred

Responsibilities

  • Leverage Business Intelligence tools to design and build interactive dashboards. Develop clear, insightful visualizations that track key performance and risk indicators, diagnose issues, surface data‑driven solutions, and empower stakeholders to make informed, timely decisions.
  • Perform comprehensive analysis of complex datasets to identify trends, patterns, and anomalies. Translate findings into actionable insights that support data‑enabled decision‑making and drive continuous improvement across the organization.
  • Identify high‑value opportunities to apply advanced analytics, including Machine Learning and AI, to solve business challenges, improve performance, and mitigate risks. Develop predictive models and other advanced analytical solutions to uncover deeper insights and support strategic initiatives. Support experimentation, A/B testing, and model performance monitoring.
  • Support the design and implementation of automated processes to streamline workflows and reporting. Improve operational efficiency, reduce manual effort, and ensure consistent, accurate, and timely data delivery through automation.
  • Gather and evaluate specific data requirements from business stakeholders including executive members, propose tailored data solutions through analytics, and effectively communicate these solutions.
  • Create effective presentation decks to present data analysis results to stakeholders and management.
  • Promote data analytics best practices and technology adoption within the organization.
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