Vice President Jobs

About The Position

Requirements

• Advanced degree in data science or quantitative/STEM field required, PHD preferred. 3+ years’ experience preferred in data science, or quantitative field (inclusive of PHD work). Experience with Financial data, particularly Investment management data, a plus.
• Clear, concise and effective communicator.
• High attention to detail with very strong analytical & critical thinking skills.
• Experience with data science/machine learning algorithms and tools (R, Python, or AI platforms) required. Experience with data workflow/ETL development tools (preferably Alteryx, Dataiku). Experience with dashboard/visualization development tools (Tableau, Power BI, D3.JS).Experience with cloud data warehouse solutions (preferably Snowflake) and CRM/analytics tools (Salesforce, Sigma).
• Self-motivated and operates with an ownership mentality.
• Provides work guidance to less experienced colleagues, but no direct reports initially. Opportunity for advancement and expected to lead analytical projects of a highly complex scope.

Responsibilities

• Independently conduct advanced, complex analyses of internal and external client or industry data sources and lead the development of statistical models and/or machine learning algorithms for analyzing and predicting client behavior, securities performance, risk or economic data. Able to independently gather requirements, provide leadership to devise analytical solutions and execute implementation of assigned tasks.
• Conducts metric analysis, leads data modeling and uses technology applications, applying techniques such as SQL querying and automated data workflow development to extract, blend and standardize numerous data sources for populating models. Program and/or system configure sophisticated models or algorithms. Expected familiarity with applied machine learning techniques and numerous machine learning algorithms, including classification and regression algorithms, market basket analysis, etc., for client segmentation purposes, tactical opportunity analysis and sales strategy enhancements.
• Formulates findings, prepares reports, including development of dashboards and visualizations to deliver results to management and sales staff. Provides recommendations for addressing observed outcomes. Translate complex technical concepts and analyses to non-technical audiences, including sales mgmt.
• Serves as a resource to colleagues unfamiliar with specialized process or data sets. Stays abreast of latest data science and analytics technologies, and market trends. Partners with management to evaluate and select the most appropriate technologies.

Benefits

• highly competitive compensation
• benefits
• wellbeing programs
• generous paid leaves
• paid volunteer time