Financial Data Scientist (Machine Learning)
Carlyle Group - Washington, DC
posted 2 days ago
About the position
We are looking for qualified individuals who are eager to solve difficult problems to join us. The 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.
Responsibilities
- Design and implement Machine Learning models for predictive analytics in the private equity sector, encompassing the full lifecycle from exploratory data analysis to deployment.
- Continuously analyze and refine model performance. Ensure robust testing, effective deployment, and ongoing maintenance in a production environment.
- Identify, analyze, and interpret complex data trends within private equity markets, contributing to data-driven decision-making.
- Collaborate with data engineers to enhance data pipelines and automate processing tasks; and with Quant Researchers to validate the backtests.
- Communicate project statuses, findings, and recommendations effectively with diverse stakeholders.
- Stay abreast of the latest in statistical and ML techniques, particularly those relevant to financial markets and private equity.
Requirements
- Bachelor's degree, required
- Concentration in a STEM field, strongly preferred
- Master's degree in Computer Science, Data Science, Statistics, Mathematics, or related field preferred.
- At least 3+ years of relevant experience in data science or machine learning, required
- Experience in finance or private equity, strongly preferred
- Expertise in Python and its data-related libraries (e.g., Numpy, Pandas, Scikit-learn).
- Deep understanding of ML algorithms for time series analysis and model selection.
- Proficiency in SQL and experience with cloud computing (AWS preferred).
- Demonstrated experience in managing ML models in production, including aspects like scaling and monitoring.
- Strong analytical, problem-solving, and communication skills.
- Familiarity with MLOps tools and practices is a plus.
Benefits
- Comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs.
- Eligibility to participate in an annual discretionary incentive program, dependent on various factors, including individual and organizational performance.
