We are working on behalf of a boutique hedge fund based in New York City, specializing in fundamental L/S equity strategies. Who leverage innovative data sources to gain a competitive edge in the financial markets.
We are seeking a highly skilled and motivated Alternative Data Scientist to join the Data team. The ideal candidate will possess a strong background in data science, with a particular focus on alternative data sources. You will play a crucial role in identifying, acquiring, and analyzing novel data sets to generate actionable insights and enhance our investment strategies.
Key Responsibilities:
- Identify, evaluate, and source alternative data sets from a variety of industries and providers. Integrate these data sets with existing internal databases and systems.
- Conduct exploratory data analysis, statistical modeling, and machine learning on large, complex data sets to uncover patterns, trends, and investment opportunities.
- Develop predictive models and trading signals using alternative data to support the firm's investment decisions.
- Work closely with portfolio managers, analysts, and other data scientists to incorporate alternative data insights into the investment process.
- Ensure the accuracy, reliability, and timeliness of alternative data sources. Develop and implement processes to maintain data quality and address any issues.
- Stay current with industry trends, emerging technologies, and best practices in alternative data science. Continuously seek out new data sources and methodologies to enhance the firm’s competitive edge.
Qualifications:
- Education: Master’s or Ph.D. in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Experience: 3+ years of experience in data science or a related field, preferably within the financial services industry.
Technical Skills:
- Proficiency in programming languages such as Python, R, or similar.
- Experience with data analysis tools and libraries (e.g., Pandas, NumPy, Scikit-learn).
- Knowledge of SQL and database management.
- Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, GCP).
- Analytical Skills: Strong analytical and quantitative skills with a demonstrated ability to apply statistical and machine learning methods to real-world data.
- Communication: Excellent verbal and written communication skills, with the ability to present complex findings in a clear and concise manner.
- Problem-Solving: Proven ability to independently tackle complex problems and deliver innovative solutions.
- Attention to Detail: High degree of accuracy and attention to detail.
Preferred Qualifications:
- Experience working with alternative data sources such as satellite imagery, social media data, web scraping, or transactional data.
- Knowledge of financial markets, investment strategies, and quantitative finance.
- Familiarity with visualization tools such as Tableau, Power BI, or D3.js.
