Senior Data Science Leader
4 days ago
**Job Summary:**
We are seeking an experienced Senior Data Science Leader to join our team in Manhattan. As a key member of our organization, you will lead our data science efforts and collaborate with our investment professionals to develop innovative solutions.
The ideal candidate will have a strong background in data science, machine learning, and statistics, with experience in working with large structured and unstructured data sets. You will be responsible for designing and building data science tools and infrastructure to enable our firm to make better business and investment decisions.
We offer a competitive salary of $250,000 per year, as well as a range of benefits including health insurance, retirement savings, and paid time off.
Responsibilities:
- Lead data science efforts and develop innovative solutions
- Collaborate with investment professionals to design and build data science tools and infrastructure
- Analyze complex data sources and develop predictive and analytical models
- Advise on smarter data utilization and drive developments in advancing big-data and analytic services
- Develop attribution, segment, and predictive models to support business, investment, and portfolio company strategies
- Seek data from, gains opinions on industry trends, issues, and solutions
Requirements:
- 8+ years of relevant background as a Data Scientist, Quantitative Researcher or Financial Engineer within the Investment Community
- Extensive experience in a data-driven professional setting, preferably from a private credit, private equity, investment management or investment banking organization
- Strong academic record and a BA/BS or Master's degree with high mathematical and computing content (e.g., Computer Science, Statistics, Mathematics, Engineering or Physics)
- Fluency in the languages of data manipulation (e.g., SQL) and statistical analysis (e.g., R or Python/NumPy), with ability to code (e.g., PHP) a plus
- Experience in working with large structured and unstructured data sets, with comfort in combining disparate and diverse structured and unstructured data sources
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