Data Science Intern

Benefits

Parental leave

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Non-birth-parent leave

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Family-building benefits

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• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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401(k) match

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Market context

Median wage (BLS OEWS)

$111,944 national median

Projected growth (BLS Employment Projections)

+13.7% - Much faster than average

Matched to SOC 15-1252 - Data and ML aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Schedule

Shift type

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Weekend work

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Application

Cover letter

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Assessment

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Deadline

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Where they hire

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About this role

Data Science Intern Beijing OR Shanghai WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies - the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it. THE ROLE 岗位职责: WorldQuant is seeking exceptional individuals to join the firm as a Data Science Intern. While prior finance experience is not required, a successful candidate must possess a strong interest in learning about finance and global markets. - Perform analysis and generate models of financial datasets using machine learning techniques 运用机器学习的方法分析并构建金融数据模型 - Verify the integrity of unstructured data and turn data into potentially valuable insights 验证非结构化数据的价值并将数据转化成潜在的高质量的市场洞见 - Develop and create data that seek to predict the movement of financial market by applying variety of algorithmic techniques 应用各种算法技术开发并构建可尝试预测金融市场波动的数据 WHAT WE OFFER 你将会获得: - Join our established

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