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# Data Scientist

- **Company:** HOLLISTER INC
- **Location:** Cambridge, MA, United States
- **Salary:** $208,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Big Data, Python (Programming Language), Linear Regression, Machine Learning, Natural Language Processing, Information Technology, Software Coding
- **Published:** September 15, 2026
- **Apply:** https://find.jobs/jobs-near-me/apply/ats-redirect/?id=2970823474-2

## About the Role

* Bachelor's degree or concentration in a highly quantitative or relevant data science field (Computer Science, Statistics, Mathematics, Finance, etc.) or equivalent professional experience
 * Experience with machine learning or adjacent fields (natural language processing, random forests, linear regression, predictive modeling, and entry-level data science concepts)
 * Experience writing code in Python
 * Experience handling terabyte-sized datasets, discovering hidden patterns, and working with managers to develop models
 * Excitement for the venture capital and private equity space and the opportunity to make analytical and data-driven decisions
 * Location: This role requires 3 days per week in our clients office in NYC.

## Description

Our client is seeking a talented Data Scientist to join their team as an independent remote employee. Our team brings data science and machine learning to the private equity investment process, providing unparalleled access to alternative data sources and proprietary data from portfolio companies. You'll be at the forefront of high-value tactical workflows that drive all aspects of the investment process. As a Data Scientist with our client, you'll have the opportunity to own due diligence processes, source efforts, or portfolio support initiatives, with your work influencing billions of dollars in investment decisions. You'll work in a collaborative, fast-moving team in close collaboration with experienced professionals passionate about AI/ML and its impact on the private equity space., * Develop predictive models and proprietary analytics from large datasets using advanced queries, filters, and data visualization tools

 * Create valuable insights from datasets directly with stakeholders
 * Architect and manage analytical projects from ideation to launch
 * Leverage alternative data sets to algorithmically determine the best investments for our clients
 * Conduct competitive analysis to determine the soundness of investments using all relevant data sources
 * Use ground-truth data from portfolio companies to improve business outcomes (automated lead generation/enrichment, forecast and churn modeling, etc.)