Data & Analytics - Assistant Vice President

Institutional Capital Network, Inc. d/b/a iCapital

AVP, Data and Analytics

New York, NY

In-office role

Responsibilities: Own, develop and evangelize data-driven thinking and analysis across the organization. Sit in the data team and be the primary point-of-contact for all analytical needs. Write Python and SQL (in dbt) to extract, transform, validate, and aggregate data. Create Tableau dashboards for business teams, charting key metrics and performing exploratory data analysis. Develop statistical models and construct data-driven experiments. Convert data insights into concrete, action-oriented and phased execution plans that measurably grow various business metrics over time. Work closely with our engineering, product and business teams to form a thorough understanding of our industry and evolving data models. Drive projects to completion by gathering business requirements, implementing technical solutions, following software best engineering practices, and present on results. Analyze data, respond to client requests, and turn insights into action. Understand complex business problems, scope projects, identify operational bottlenecks, optimize workflows, and communicate findings across all levels of the organization. Develop dashboards for various business teams, charting key metrics and extracting data-driven insights. Serve as the primary point-of-contact for all business teams (including answering technical questions, serving client requests, troubleshooting suspect data, and spearheading new analyses). Grow data insights into concrete execution plans by scoping requirements, feasibility, cost-benefit, governance, dependencies, telemetry, and adoption.

Salary: $139,000 – $155,000/year

This is an in-office role based in our New York City office. 

Requirements: Master's Degree in Computer Science, Data Science, or related field and three years in the job offered or three years business intelligence/data analytics. Experience must include two years each of the following: gathering business requirements; open-source technologies or object-oriented/functional programming; data collection, manipulation, and reconciliation; designing data visualizations utilizing business intelligence tools such as Tableau, Looker, PowerBI, or QuickSight; monitor data pipeline failures; OLAP/OLTP databases; writing code; and database design. Experience must include one year numeric research framework such as Python/Pandas, and AWS. Experience may be gained concurrently.