We are looking for qualified individuals who are eager to solve difficult problems to join us. The newly created data science team falls under global private equity. We leverage modern techniques like big data, and machine learning to build industrial-level solutions to facilitate investment decision-making. As part of a small team made of individuals from diverse backgrounds, we believe everyone is an integral part of the team's success. Using the analogy of practicing alchemy, we will have math, computer science, and domain knowledge of finance at our disposal to create something truly valuable. You will not only work with top talents within the private equity industry, but also work hand-in-hand with teammates previously work for top technology companies. Instead of fixing and maintaining large systems, you will be the pioneer to truly build something from scratch and put it into use.
- Documentation and testing to ensure fully reproducible research
- Develop solutions to ensure model output is explainable and interpretable
- Work with engineers to deploy solutions into production
- Hypothesis testing, statistical analysis and modeling (time series data with structured and unstructured data, graph analysis, supervised learning)
- Independently conduct data discovery, descriptive and predictive analysis
- Work with stakeholders to understand the business context
- "Make sure the data is always good"
Education & Certificates
- College degree and above in STEM field (master or PhD preferred)
- 3 ~ 6 years of hands-on Machine Learning experience
Competencies & Attributes
- Strong verbal and written communication skills
- Comfortable with public presentation and storytelling
- Curiosity with a can-do attitude
- Technical Requirements (following order of importance):
- Expert in mathematical theory and engineering practice behind common ml techniques (regression, classification, time series, neutral network etc.)
- Familiarity with statistics, probability, and hypothesis testing
- Hands-on experience with ML framework (pytorch, tensorflow, scikit-learn)
- SQL (ANSI or common RDBMS)
- Experience deploying models in production - online/offline inferencing
- Good to have:
- Cloud computing (AWS preferred)
- Familiarity with finance - private equity, asset valuation
The Carlyle Group (NASDAQ: CG) is a global investment firm with $373 billion of assets under management and more than half of the AUM managed by women, across 543 investment vehicles as of December 31st, 2022. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world's largest and most successful investment firms, with more than 2,100 professionals operating in 29 offices in North America, South America, Europe, the Middle East, Asia and Australia. Carlyle places an emphasis on development, retention and inclusion as supported by our internal processes and seven Employee Resource Groups (ERGs). Carlyle's purpose is to invest wisely and create value on behalf of its investors, which range from public and private pension funds to wealthy individuals and families to sovereign wealth funds, unions and corporations. Carlyle invests across three segments - Global Private Equity, Global Credit and Investment Solutions - and has expertise in various industries, including: aerospace, defense & government services, consumer & retail, energy, financial services, healthcare, industrial, real estate, technology & business services, telecommunications & media and transportation.
At Carlyle, we know that diverse teams perform better, so we seek to create a community where we continually exchange insights, embrace different perspectives and leverage diversity as a competitive advantage. That is why we are committed to growing and cultivating teams that include people with a variety of perspectives, people who provide unique lenses through which to view potential deals, support and run our business.