Data Science Quantitative Modeling Lead

Key Skills

Data Architecture, Data Modeling, Data science techniques, Design, Java Programming, Python Programming, SQL

Job Description

CCOR Technology & Cybersecurity (“CCOR Tech & Cyber) is a group within the Compliance, Conduct and Operational Risk (CCOR) organization and has areas of alignment across all Lines of business (LOBs), Regions and Corporate Functions (CFs), responsible for the independent oversight of first line operational risk management practices and compliance with technology and cybersecurity laws, rules, and regulations. Additionally, CCOR Tech & Cyber provides Firmwide end-to-end independent second line coverage of Technology and Cybersecurity Compliance, Resiliency and Crisis Management, Insider Threat, and Global Supplier Services.

Technology and Cybersecurity Operational Risk Management – Data Scientist Executive Director:

The Global Technology Infrastructure organization delivers foundational infrastructure for critical application workloads across multiple lines of business. The GTI Technology and Cybersecurity Operational Risk Management team monitors and tests for risks and control deficiencies within multiple GTI products, services, and processes.

The Data Scientist Executive Director reports directly into Data Science director of Technology and Cybersecurity Operational Risk Management and is responsible for development of methodologies to analyze qualitative and quantitative data and synthesize insights from multiple sources to identify potential areas of risk. The Data Scientist Executive Director will be accountable for both business and technology partners to identify and derive data of interest. The candidate will work in a collaborative and thought-provoking environment, and engage with a diverse set of stakeholders globally in an effort to drive actionable insights. The Data Scientist Executive Director will directly support the GTI Technology Operational Risk Officer and is will be responsible for quantitative and statistical analysis to help identify risks associated with technology maintenance across GTI infrastructure including AWS, Google, Microsoft, and internal cloud infrastructure.

Key responsibilities include:

• Collaborate across technical and risk oversight teams to deliver data-driven insights, recommendations, and solutions that solve critical business risk oversight challenges
• Lead the research and development of data science initiatives to deliver these insights and solutions
• Manage the relationship with internal clients, gathering requirements, understanding business domain, presenting results, and developing a trusted adviser relationship
• Manage the lifecycle of data science project, including ideation, data acquisition, exploration, model design, prototyping, and pathway to productionization
• Partner with the engineering and data platform teams on the creation of capabilities which accelerate data science delivery and operationalization
• Work independently and collaboratively (as needed) within the team to achieve the desired outcomes of data science efforts

Qualifications:

• 15+ years of experience with data science, quantitative/statistical modeling, data engineering with the focus on analytics and machine learning
• Bachelor’s Degree in relevant technical or quantitative fields (e.g., Mathematics, Engineering, Finance, Business, Physics, Statistics, Operations Research and Economics); graduate degree a plus
• Proven analytical and statistical skills applied to advanced analytics, modeling, machine learning
• Proficiency in multiple modern programming languages, including skills in Python, SQL at a minimum
• Strong visualization skills and familiarity with BI / user interface tools
• Experience delivering data science capabilities on a cloud platform
• Expertise in application, data, and infrastructure architecture disciplines
• Knowledge of industry-wide technology trends and best practices
• Knowledge of second-line operational risk management and compliance practices, and associated control principles
• Passionate about building an innovative culture
• Ability to collaborate with high-performing teams and individuals througho

  The CCOR Data and Analytics team seeks a candidate who is passionate about solving business problems through innovation and contemporary best practices in data science. The CCOR Data Scientist will develop methodologies to analyze qualitative and quantitative data and synthesize data from multiple sources to identify potential areas of risk. The CCOR Data Scientist will coordinate with both business and technology partners to identify and derive data of interest. The candidate will work in a collaborative and thought-provoking environment, and engage with a diverse set of stakeholders globally in an effort to drive actionable insights.

  Responsibilities include:

  • Collaborate across CCOR, as well as other data teams in the first-line, to deliver data-driven insights, recommendations, and solutions that solve important business problems
  • Lead the research and development of data science initiatives to deliver these insights and solutions
  • Manage the relationship with internal clients, gathering requirements, understanding business domain, presenting results, and developing a trusted adviser relationship
  • Manage the lifecycle of data science project, including ideation, data acquisition, exploration, model design, prototyping, and pathway to productionization
  • Partner with the engineering and data platform teams on the creation of capabilities which accelerate data science delivery and operationalization
  • Work independently and collaboratively (as needed) within the team to achieve the desired outcomes of data science efforts

  Qualifications:

  • Bachelor’s Degree in relevant technical or quantitative fields (e.g., Mathematics, Engineering, Finance, Business, Physics, Statistics, Operations Research and Economics); graduate degree a plus
  • Proven analytical and statistical skills applied to advanced analytics, modeling, machine learning
  • Proficiency in multiple modern programming languages, including skills in Python, SQL at a minimum
  • Strong visualization skills and familiarity with BI / user interface tools
  • Experience delivering data science capabilities on a cloud platform
  • Expertise in application, data, and infrastructure architecture disciplines
  • Knowledge of industry-wide technology trends and best practices
  • Knowledge of second-line operational risk management and compliance practices, and associated control principles
  • Passionate about building an innovative culture
  • Ability to collaborate with high-performing teams and individuals throughout the firm to accomplish common goals
  • Demonstrated verbal and written communication skills
  • Strong organizational and multi-tasking skills with demonstrated ability to manage expectations
  ut the firm to accomplish common goals
• Demonstrated verbal and written communication skills
• Strong organizational and multi-tasking skills with demonstrated ability to manage expectations