Institutional Capital Network

Data Analytics - Associate

Institutional Capital Network · New York, NY
New York, NY was $110K–$140K Closed
Applications are closed for this role. It was originally posted 2026-09-21. It’s no longer accepting applicants — see roles Institutional Capital Network is still hiring for →, or browse the live openings below.
Salary
$110K–$140K
Type
Full-time
Experience
3+ yr

About the Role

iCapital is looking to hire an Analytics Engineer Associate to measurably drive growth for the business teams using analytics, data science and machine learning. This role will work with our Sales, Marketing and Product groups to define, calculate and grow their key operating metrics (i.e. sales conversion, marketing conversion, product adoption, CAC/CLTV). This individual will sit in the Analytics group of the broader Chief Data Office (CDO) team and work closely with the Business Intelligence, Data Engineering and Machine Learning teams.

This is a technical, individual contributor role that blends data engineering, data analytics, data science and machine learning. The ideal candidate will be able to understand complex business problems, interface with internal stakeholders, develop execution plans, implement all aspects of the project technically, and finally present on their work.

Responsibilities

  • Write Python and SQL (in dbt) to extract, transform, validate, and aggregate data.
  • Conduct exploratory data analyses, build machine learning models and develop ML infra in Jupyter and Python.
  • Develop statistical models and construct data-driven experiments (e.g. A/B tests).
  • Visualize key metrics using Tableau.
  • Work closely with our engineering, product and business teams to form a thorough understanding of our industry and evolving data model.
  • Build data sets using dbt and SQL, visualize measures of success using Tableau, formulate exploratory data analyses using pandas and Jupyter, develop statistical and machine learning models using Python, and finally deploy production-ready code using GitLab.
  • Gather requirements from internal stakeholders, conduct exploratory data analyses, perform statistical inference, and deploy machine learning models to production.

Qualifications

  • Bachelor’s degree or higher in computer science, economics, mathematics, statistics or a related technical field
  • 3-5 years of experience in an data-related role
  • Excellent knowledge of SQL (i.e. dbt experienced is preferred), Python and pandas
  • Very good knowledge of statistics, ML models and ML services and infra
  • Knowledge of data modeling, relational databases, normalization, OLAP stores
  • Strong writing, communication and presentation skills
  • Familiar with a business intelligence tool (e.g. Tableau, Looker, PowerBI)
  • Experience in the financial services and alternative investments space is preferred
  • Experience with product or marketing analytics (i.e. adoption or retention analyses, customer journey, user segmentation, CLTV and CAC calculations, conversion funnels)

Benefits

The base salary range for this role is $110,000 to $140,000. iCapital offers a compensation package which includes salary, equity for all full-time employees, and an annual performance bonus. Employees also receive a comprehensive benefits package that includes an employer matched retirement plan, generously subsidized healthcare with 100% employer paid dental, vision, telemedicine, and virtual mental health counseling, parental leave, and unlimited paid time off (PTO).

We believe the best ideas and innovation happen when we are together. Employees in this role will work in the office Monday-Thursday, with the flexibility to work remotely on Friday.

For additional information on iCapital, please visit https://www.icapitalnetwork.com/about-us   Twitter: @icapitalnetwork | LinkedIn: https://www.linkedin.com/company/icapital-network-inc | Awards Disclaimer: https://www.icapitalnetwork.com/about-us/recognition/

iCapital is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, gender, sexual orientation, gender identity, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

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