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For Companies At a Glance
- Tasks: Join our team to analyse complex datasets and drive investment strategies.
- Company: Carlyle Group is a leading global investment firm with a focus on diversity and inclusion.
- Benefits: Enjoy a collaborative culture, mentorship opportunities, and the chance to impact real investment decisions.
- Why this job: Make a tangible impact in investment processes while working with cutting-edge AI tools.
- Qualifications: Bachelor's degree in STEM and 6+ years in data engineering or related fields required.
- Other info: Work in a dynamic environment with a commitment to diverse perspectives and innovative solutions.
The predicted salary is between 43200 - 72000 £ per year.
Basic information
Job Name:
Investment Data Scientist
Location:
London
Line of Business:
Data Science
Job Function:
Investor Services
Date:
Wednesday, July 9, 2025
Position Summary
Join our dynamic Investment Data Science Team as a Data Scientist and immerse yourself in the heart of the investment process. This unique role fuses technical data science expertise with sharp commercial insight, placing you at the crossroads of investment decision-making and value creation. Collaborate closely with our investment teams and company leaders, leveraging your skills to make a tangible impact in due diligence and growth strategies.
Responsibilities
- Develop scalable diligence analyses for thorough investment due diligence, balancing swift execution with meticulous analysis to assess potential risks and opportunities.
- Own diligence data domain and development of new scalable analyses for diligence insights
- Partner with AI product team to further develop AI diligence platform giving business insight and feedback on usability
- Own execution of company diligences and delivery end to end using AI platform and tools
- Mentor and be a technical manager for individual contributor Investment Data Scientists
- Lead in developing and implementing data-centric strategies and tools, enhancing our investment processes and supporting our deal teams.
- Provide critical support in live due diligence, translating complex data into comprehensive analysis under tight deadlines.
- Engage in sophisticated data analysis, including feature engineering and analytics.
- Cleanse, integrate, and interrogate diverse datasets to unearth unique insights.
- Conduct rigorous hypothesis testing, statistical analysis, and modeling.
- Develop and own short-term roadmap for diligence analysis improvements and new analyses
- Take investment team feedback incorporating it with near-term roadmap to improve diligence outcomes
- Work with upstream partners on data and insight teams to add new features to diligence analyses and ensure data cleansing and availability is sufficient
What you\’ll do:
- Navigate and analyze complex datasets, extracting key insights to guide investment strategies.
- Collaborate with internal teams and external executives on data-driven growth initiatives.
- Manage third-party resources, integrating external expertise into our internal framework.
- Spearhead the creation of innovative data tools and products to scale our deal support capabilities.
Qualifications
Education & Certificates
- A bachelor\’s degree or higher in a STEM field, required
- Concentration in Computer Science, Math, Physics or other engineering related field, preferred
Professional Experience
- At least 6 years of experience in data engineering or a related discipline, with a proven track record of success.
- Experience in commercial consulting, investment banking, or client-oriented roles is advantageous.
- Experience in the financial services or private equity industry, preferred
Competencies & Attributes
- Exceptional problem-solving abilities.
- Aptitude for translating data into actionable business strategies.
- Strong verbal and written communication skills, with a flair for public presentation and storytelling.
- Solid understanding of investment, financial valuation, and commercial growth principles.
- Advanced Python and SQL skills for complex data analysis.
- Proficient in machine learning techniques and handling large datasets.
- Skilled in data visualization and statistical modeling.
- Familiarity with AWS cloud computing and Git version control systems.
Company Information
The Carlyle Group (NASDAQ: CG) is a global investment firm with $453 billion of assets under management and more than half of the AUM managed by women, across 641 investment vehicles as of March 31, 2025. Founded in 1987 in Washington, DC, Carlyle has grown into one of the world\’s largest and most successful investment firms, with more than 2,300 professionals operating in 29 offices in North 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 Carlyle AlpInvest – 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 believe that a wide spectrum of experiences and viewpoints drives performance and success. Our CEO, Harvey Schwartz, has stated that, \”To build better businesses and create value for all of our stakeholders, we are focused on assembling leadership teams with the strongest insights from a range of perspectives.\” We strive to foster an environment where ideas are openly shared and valued. By bringing together teams with varied expertise and approaches, we enjoy a competitive advantage and create a stronger foundation for long-term success. #J-18808-Ljbffr
Investment Data Scientist employer: Carlyle
Contact Detail:
Carlyle Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Investment Data Scientist
✨Tip Number 1
Familiarise yourself with the latest trends in investment data science. Understanding how AI and machine learning are being integrated into investment strategies can give you a significant edge during interviews.
✨Tip Number 2
Network with professionals in the financial services and private equity sectors. Attend industry events or webinars to connect with potential colleagues and learn more about the company culture at Carlyle.
✨Tip Number 3
Prepare to discuss your experience with complex datasets and how you've used data to drive business decisions. Be ready to share specific examples that highlight your problem-solving skills and technical expertise.
✨Tip Number 4
Showcase your communication skills by practising how to present complex data insights clearly and concisely. This is crucial for collaborating with investment teams and conveying your findings effectively.
We think you need these skills to ace Investment Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science, investment analysis, and any specific skills mentioned in the job description, such as Python, SQL, and machine learning techniques.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and investment. Mention how your background aligns with the responsibilities of the role and provide examples of past successes that demonstrate your problem-solving abilities.
Showcase Technical Skills: Clearly outline your technical skills in your application. Include specific projects or experiences where you used advanced data analysis, statistical modeling, or data visualization to drive business outcomes.
Highlight Collaboration Experience: Since the role involves working closely with investment teams and external executives, emphasise any previous collaborative projects. Describe how you contributed to team success and how you communicated complex data insights effectively.
How to prepare for a job interview at Carlyle
✨Showcase Your Technical Skills
As an Investment Data Scientist, you'll need to demonstrate your advanced Python and SQL skills. Be prepared to discuss specific projects where you've used these tools for complex data analysis, and consider bringing examples of your work to showcase your capabilities.
✨Understand the Investment Landscape
Familiarise yourself with the financial services and private equity industries. During the interview, be ready to discuss how your data insights can influence investment strategies and decision-making processes, showing that you understand the commercial implications of your analyses.
✨Prepare for Problem-Solving Scenarios
Expect to face problem-solving questions that assess your analytical thinking. Practice articulating your thought process clearly, as this role requires exceptional problem-solving abilities. Use the STAR method (Situation, Task, Action, Result) to structure your responses.
✨Communicate Effectively
Strong verbal and written communication skills are crucial for this role. Prepare to explain complex data findings in a way that is accessible to non-technical stakeholders. Practising storytelling techniques can help you convey your insights compellingly during the interview.
