Chief Data Scientist
Finance Across Borders · United States
- On site
- Part-time
- United States
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About the role
Company Description Finance Across Borders is a global student-led finance club at HULT International Business School, focused on expanding members’ financial knowledge and practical skills. The club provides learning opportunities, workshops, and discussions that help members better understand global financial markets and industry practices. It emphasizes networking with peers, alumni, and professionals to support career development. By combining education, collaboration, and real-world exposure, Finance Across Borders aims to prepare students for successful careers in finance-related fields.
Role Description The Chief Data Scientist role at Finance Across Borders is a part-time remote position. This role is responsible for designing and implementing data-driven approaches to analyze financial markets, club activities, and member engagement. Day-to-day tasks include collecting and cleaning data from various sources, building analytical models, and identifying patterns that can inform educational content, events, and strategic initiatives. The Chief Data Scientist will collaborate with club leadership to translate insights into actionable recommendations, create visualizations and reports for stakeholders, and guide the use of data tools and methodologies across the organization.
Qualifications
Role Description The Chief Data Scientist role at Finance Across Borders is a part-time remote position. This role is responsible for designing and implementing data-driven approaches to analyze financial markets, club activities, and member engagement. Day-to-day tasks include collecting and cleaning data from various sources, building analytical models, and identifying patterns that can inform educational content, events, and strategic initiatives. The Chief Data Scientist will collaborate with club leadership to translate insights into actionable recommendations, create visualizations and reports for stakeholders, and guide the use of data tools and methodologies across the organization.
Qualifications
- Strong foundation in Computer Science and Data Science, with the ability to design and implement data pipelines and analytical solutions.
- Proficiency in Statistics and Analytical Skills to interpret complex datasets and support evidence-based decision-making.
- Experience with Pattern Recognition to detect trends in financial data and member engagement metrics.
- Familiarity with data analysis tools and programming languages (e.g., Python, R, SQL) and visualization platforms (e.g., Tableau, Power BI).
- Ability to communicate technical findings clearly to non-technical audiences and collaborate in a diverse, student-led environment.
- Interest in finance, financial markets, and quantitative methods; prior involvement in finance clubs or projects is an advantage.
- Currently enrolled in or having completed studies in a relevant field such as Data Science, Computer Science, Statistics, Finance, or a related discipline.
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