Position Summary
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.
Primary Responsibilities:
- Model Development & Implementation: Design and implement Machine Learning models for predictive analytics in the private equity sector, encompassing the full lifecycle from exploratory data analysis to deployment.
- Model Optimization & Management: Continuously analyze and refine model performance. Ensure robust testing, effective deployment, and ongoing maintenance in a production environment.
- Data Analysis & Insight Generation: Identify, analyze, and interpret complex data trends within private equity markets, contributing to data-driven decision-making.
- Collaboration & Technical Leadership: 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.
- Industry Trend Awareness & Skill Development: Stay abreast of the latest in statistical and ML techniques, particularly those relevant to financial markets and private equity.
Requirements:
Education & Certifications:
- 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.
Professional Experience:
- At least 3+ years of relevant experience in data science or machine learning, required
- Experience in finance or private equity, strongly preferred
Technical Competencies & Attributes:
- 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
Benefits/Compensation
The compensation range for this role is specific to Washington, D.C. and takes into account a wide range of factors including but not limited to the skill sets required/preferred; prior experience and training; licenses and/or certifications.
The anticipated base salary range for this role is $140,000 to $160,000.
In addition to the base salary, the hired professional will enjoy a comprehensive benefits package spanning retirement benefits, health insurance, life insurance and disability, paid time off, paid holidays, family planning benefits and various wellness programs. Additionally, the hired professional may also be eligible to participate in an annual discretionary incentive program, the award of which will be dependent on various factors, including, without limitation, individual and organizational performance.
Due to the high volume of candidates, please be advised that only candidates selected to interview will be contacted by Carlyle.
Company Summary
The Carlyle Group (NASDAQ: CG) is a global investment firm with $382 billion of assets under management and more than half of the AUM managed by women, across 600 investment vehicles as of September 30, 2023. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world's largest and most successful investment firms, with more than 2,200 professionals operating in 28 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.
- Seniority Level
- Mid-Senior level
- Industry
- Financial Services
- Employment Type
- Full-time
- Job Functions
- Information Technology
- Skills
- Data Science
- Predictive Analytics
- Exploratory Data Analysis
- Data Analytics
- Model Selection
- Pattern Recognition
- Machine Learning
- Artificial Intelligence (AI)
- Time Series Analysis
