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# Data Scientist, Portfolio Optimization

- **Company:** EQUAL OPPORTUNITY FOUNDATION, INC
- **Location:** San Francisco, CA, United States
- **Experience:** Starter
- **Salary:** $154,500.0 - $202,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Airflow, Data Deduplication, Data Visualization, Python (Programming Language), NumPy, SciPy, Data Processing, Large Language Models, Pandas, Plotly, Machine Learning Operations, Streamlit Framework, Data Pipelines
- **Published:** July 17, 2026
- **Apply:** https://www.dice.com/job-detail/5928a31a-608d-42a2-9f2e-5fc3826a9a6e

## About the Role

* PhD in a quantitative field (statistics, finance, physics, computational science, engineering, or related)
 * 1-3 years in a quantitative research, data science, or analytics role in life sciences or life science adjacent field (healthcare, academic research, or consulting all count; substantive internships qualify)
 * Strong Python programming skills with experience in data-intensive workflows (pandas, numpy, scipy)
 * Solid grasp of core portfolio construction and risk concepts: position sizing, rebalancing, Sharpe ratio, drawdown, volatility, benchmark comparison
 * Demonstrated ability to work with messy, real-world datasets - comfortable with data wrangling, deduplication, and quality assessment
 * Clear communicator who can present quantitative results to both technical peers and business stakeholders, * Experience with backtesting frameworks or portfolio simulation (vectorbt, Backtrader, or custom implementations)
 * Exposure to healthcare, pharma, or biotech data (clinical trials, claims data, -omics, real-world evidence)
 * Familiarity with alternative data in a research or investment context
 * Experience with probability-of-success modeling, drug development decision analysis, or health economics
 * Comfort with LLMs or AI/ML pipelines in a production or research setting
 * Familiarity with dashboard/visualization tools (Streamlit, Plotly, Dash) and pipeline orchestration (Dagster, Airflow)

Healthcare OR finance domain knowledge is valued; both are not required.

## Description

* Work with the team to implement and maintain core portfolio engine: order management system, execution simulation layer, portfolio construction service, and performance tracking
 * Design risk frameworks that quantify exposure across a portfolio of drug development bets with radically different risk profiles, timelines, and failure modes
 * Run rigorous backtesting experiments with strict temporal constraints to evaluate Formation strategies against baseline approaches and measure marginal signal from new evidence sources
 * Coordinate across the organization to integrate internal Formation data sources (clinical trial data, genomic evidence, real-world data) and proprietary tooling into portfolio analytics pipelines
 * Work with product and engineering teams to build dashboards and reporting that communicate portfolio performance, risk metrics, and strategy comparisons to both technical and executive stakeholders
 * Collaborate with the broader data science team to ensure portfolio-level evaluation feeds back into model improvement and evidence prioritization


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