iCapital is powering the world’s alternative investment marketplace. Our financial technology platform has transformed how advisors, wealth management firms, asset managers, and banks evaluate and recommend bespoke public and private market strategies for their high-net-worth clients. iCapital services approximately $176 billion in global client assets invested in 1,433 funds, as of December 2023.
iCapital has been named to the Forbes Fintech 50 for seven consecutive years (2018-2023); a three-time selection by Forbes to its list of Best Startup Employers (2021-2023); and a three-time winner of MMI/Barron’s Solutions Provider award (See link below).
About the Role
iCapital is looking for an Analytics Engineer to help drive measurable growth across our business teams at iCapital using data. This role will work with our Sales, Marketing, and Product teams to define, calculate, and grow their key operating metrics (e.g. sales, conversions, retention). This individual will conduct exploratory data analysis, statistical analysis, and predictive modeling of the data.
At a technical level, this role will create SQL data models in dbt, perform EDA in pandas, build ML models and libraries in Python, and visualize success metrics in Tableau, all in about equal proportion.
This is a technical, individual contributor role that blends data engineering, data analytics and data science. Our technical stack includes Snowflake, dbt, Python and Tableau. This position sits within the Analytics team of the broader Data & Analytics department and work closely with our Data Engineering, Business Intelligence, and Machine Learning teams.
Responsibilities
- Write SQL (in dbt) to transform, validate, enrich, and aggregate our data.
- Iterate on ML model development (model selection/evaluation, feature engineering, hyperparameter tuning).
- Develop ML libraries to accelerate development workflow (versioning, tracking, visualization, and explainability).
- Conduct and interpret statistical analyses (hypothesis tests, regression, PCA, etc.).
- Visualize key performance metrics within Tableau.
- Work with our Data Engineering, Business Intelligence and Machine Learning teams on data infra, dashboards and ML models.
- Participate in our support rotation and SDLC release process.
Qualifications
- Very proficient in SQL and data modeling
- Very proficient in Python
- Proficient in software development (e.g. OOP, APIs, ORMs, deployment, testing)
- Proficient in statistics, ML models and ML development
- Experience with, or interest in learning, a BI tool
- 2 - 4 years of experience in a data-related role
- Bachelor’s degree or higher in computer science, mathematics, statistics, or related technical field
Benefits
The base salary range for this role is $100,000 to $130,000. 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. We offer most employees the flexibility to work in the office three or four days. Every department has different needs, and some positions will be designated in-office jobs, based on their function.
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.
ability, or other applicable legally protected characteristics.
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