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If you&#39;re excited about applying portfolio construction and risk management fundamentals to one of the most consequential prediction problems in healthcare, this is the role.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>Work with the team to implement and maintain core portfolio engine: order management system, execution simulation layer, portfolio construction service, and performance tracking</li>\n<li>Design risk frameworks that quantify exposure across a portfolio of drug development bets with radically different risk profiles, timelines, and failure modes</li>\n<li>Run rigorous backtesting experiments with strict temporal constraints to evaluate Formation strategies against baseline approaches and measure marginal signal from new evidence sources</li>\n<li>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</li>\n<li>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</li>\n<li>Collaborate with the broader data science team to ensure portfolio-level evaluation feeds back into model improvement and evidence prioritization</li>\n</ul>\n<p><strong>About You</strong></p>\n<p>We are looking for a highly motivated and experienced Data Scientist to join our team. The ideal candidate will have a strong background in data science, machine learning, and software development, with a proven track record of delivering high-quality results in a fast-paced environment.</p>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>MS or PhD in a quantitative field (statistics, finance, physics, computational science, engineering, or related)</li>\n<li>1-3 years in a quantitative research, data science, or analytics role , finance, healthcare, academic research, or consulting all count; substantive internships qualify</li>\n<li>Strong Python programming skills with experience in data-intensive workflows (pandas, numpy, scipy)</li>\n<li>Solid grasp of core portfolio construction and risk concepts: position sizing, rebalancing, Sharpe ratio, drawdown, volatility, benchmark comparison</li>\n<li>Demonstrated ability to work with messy, real-world datasets , comfortable with data wrangling, deduplication, and quality assessment</li>\n<li>Clear communicator who can present quantitative results to both technical peers and business stakeholders</li>\n</ul>\n<p><strong>Preferred Qualifications</strong></p>\n<ul>\n<li>Experience with backtesting frameworks or portfolio simulation (vectorbt, Backtrader, or custom implementations)</li>\n<li>Exposure to healthcare, pharma, or biotech data (clinical trials, claims data, -omics, real-world evidence)</li>\n<li>Familiarity with alternative data in a research or investment context</li>\n<li>Experience with probability-of-success modeling, drug development decision analysis, or health economics</li>\n<li>Comfort with LLMs or AI/ML pipelines in a production or research setting</li>\n<li>Familiarity with dashboard/visualization tools (Streamlit, Plotly, Dash) and pipeline orchestration (Dagster, Airflow)</li>\n</ul>\n<p><strong>Total Compensation Range:</strong> $154,500 - $202,000</p>\n<p>**Compensation Individual compensation is determined by several factors, including role scope, geographic location, and skills &amp; experience. Your offer will reflect where you fall within the range based on these considerations. In addition to base salary, we offer equity, comprehensive benefits, and generous perks. If the posted range doesn&#39;t match your expectations, we still encourage you to apply!</p>\n<p>**Where We Hire Formation Bio is prioritizing hiring in key hubs, primarily the New York City and Boston metro areas, with a hybrid model requiring 3 days per week in office. Applicants from the Research Triangle (NC) and San Francisco Bay Area may also be considered. Please apply only if you reside in these locations or are willing to relocate.</p>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_62b851a9-660","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Formation Bio","sameAs":"https://www.formation.bio/","logo":"https://logos.yubhub.co/formation.bio.png"},"x-apply-url":"https://job-boards.greenhouse.io/formationbio/jobs/7757667","x-work-arrangement":"hybrid","x-experience-level":"mid","x-job-type":"full-time","x-salary-range":"$154,500 - $202,000","x-skills-required":["Python","pandas","numpy","scipy","portfolio construction","risk management","backtesting","data wrangling","data visualization"],"x-skills-preferred":["backtesting frameworks","portfolio simulation","healthcare data","alternative data","probability-of-success modeling","drug development decision analysis","health economics","LLMs","AI/ML pipelines","dashboard/visualization tools","pipeline orchestration"],"datePosted":"2026-04-18T15:53:29.085Z","jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"New York, NY; Boston, MA"}},"employmentType":"FULL_TIME","occupationalCategory":"Engineering","industry":"Healthcare","skills":"Python, pandas, numpy, scipy, portfolio construction, risk management, backtesting, data wrangling, data visualization, backtesting frameworks, portfolio simulation, healthcare data, alternative data, probability-of-success modeling, drug development decision analysis, health economics, LLMs, AI/ML pipelines, dashboard/visualization tools, pipeline orchestration","baseSalary":{"@type":"MonetaryAmount","currency":"USD","value":{"@type":"QuantitativeValue","minValue":154500,"maxValue":202000,"unitText":"YEAR"}}},{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_90b91fc5-0e2"},"title":"Credit Business Analyst (MXC)","description":"<p>We are seeking a highly analytical Credit Analyst to help develop data-driven credit policies and support the growth of Jeeves&#39; global credit portfolio. 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