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For Companies At a Glance
- Tasks: Dive into data analysis to drive investment strategies and support deal teams.
- Company: Join The Carlyle Group, a leading global investment firm managing $453 billion in assets.
- Benefits: Enjoy a collaborative culture, mentorship opportunities, and the chance to work with cutting-edge AI tools.
- Why this job: Make a real impact on investment decisions while developing your data science skills in a dynamic environment.
- Qualifications: Bachelor's degree in STEM; 6+ years in data engineering; strong Python and SQL skills required.
- Other info: Ideal for those passionate about finance and data, looking to grow in a fast-paced setting.
The predicted salary is between 43200 - 72000 £ per year.
Join our dynamic Investment Data Science Team as a Data Scientist and immerse yourself in the heart of the investment process. This role combines technical data science expertise with commercial insight, positioning you at the intersection of investment decision-making and value creation. Collaborate with investment teams and company leaders to impact due diligence and growth strategies.
Responsibilities
- Develop scalable analyses for investment due diligence, balancing speed with thoroughness to identify risks and opportunities.
- Manage diligence data and develop new scalable insights.
- Partner with the AI product team to enhance the AI diligence platform, providing business insights and usability feedback.
- Execute company diligences end-to-end using AI tools and platforms.
- Mentor and lead individual contributor Investment Data Scientists.
- Develop data-centric strategies and tools to improve investment processes and support deal teams.
- Support live due diligence by translating complex data into comprehensive analysis under tight deadlines.
- Perform advanced data analysis, including feature engineering and modeling.
- Cleanse, integrate, and analyze diverse datasets for insights.
- Conduct hypothesis testing, statistical analysis, and modeling.
- Create and manage a roadmap for analysis improvements and new insights.
- Incorporate feedback from investment teams to enhance diligence outcomes.
- Collaborate with data and insight teams to add features and ensure data quality.
What you’ll do
- Analyze complex datasets to extract insights for investment strategies.
- Work with internal and external teams on data-driven growth initiatives.
- Manage external resources and integrate expertise into our processes.
- Create innovative data tools to scale deal support capabilities.
Qualifications
Education & Certificates
- Bachelor\’s degree or higher in a STEM field required.
- Concentration in Computer Science, Math, Physics, or related engineering field preferred.
Professional Experience
- Minimum 6 years in data engineering or related fields, with proven success.
- Experience in consulting, investment banking, or client-focused roles is advantageous.
- Experience in financial services or private equity preferred.
- Exceptional problem-solving skills.
- Ability to translate data into business strategies.
- Strong communication skills, including presentation and storytelling.
- Knowledge of investment, valuation, and growth principles.
- Advanced Python and SQL skills.
- Experience with machine learning and large datasets.
- Skills in data visualization and statistical modeling.
- Familiarity with AWS and Git.
Company Information
The Carlyle Group (NASDAQ: CG) manages $453 billion in assets, with a diverse global presence and a commitment to inclusion and development. Founded in 1987, Carlyle invests across various industries and segments, emphasizing value creation and stakeholder success.
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Investment Data Scientist employer: Avature
Contact Detail:
Avature 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 current market dynamics and how data influences investment decisions will help you stand out during discussions with our team.
✨Tip Number 2
Brush up on your Python and SQL skills, as these are crucial for the role. Consider working on personal projects or contributing to open-source initiatives that showcase your ability to handle large datasets and perform advanced analyses.
✨Tip Number 3
Network with professionals in the investment and data science fields. Attend relevant conferences or webinars to connect with industry experts, which could provide valuable insights and potentially lead to referrals.
✨Tip Number 4
Prepare to discuss your experience with machine learning and statistical modelling. Be ready to share specific examples of how you've applied these skills in previous roles, particularly in a financial context, to demonstrate your fit for the position.
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 engineering, investment banking, or consulting. Emphasise your technical skills in Python, SQL, and machine learning, as well as any experience with financial services.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data science and investment. Mention specific projects where you've successfully translated complex data into actionable insights, showcasing your problem-solving skills and ability to work under tight deadlines.
Showcase Your Technical Skills: Include examples of your advanced data analysis, feature engineering, and statistical modelling in your application. Highlight any experience you have with AWS and Git, as these are valuable for the role.
Prepare for Interviews: Be ready to discuss your previous experiences in detail, particularly how you've collaborated with teams to enhance business strategies. Prepare to explain your approach to managing data and developing insights that drive investment decisions.
How to prepare for a job interview at Avature
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python, SQL, and machine learning. Bring examples of past projects where you applied these skills, especially in data analysis or investment contexts.
✨Demonstrate Business Acumen
Understand the investment principles and be ready to explain how your data insights can drive business strategies. Highlight any experience you have in consulting or financial services to show your commercial insight.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Practice articulating how you would approach complex datasets and translate them into actionable insights under tight deadlines.
✨Emphasise Collaboration and Communication
Since the role involves working with various teams, be ready to discuss your experience in collaborative environments. Share examples of how you've effectively communicated complex data findings to non-technical stakeholders.
