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- Tasks: Join a dynamic team to optimise data analytics and support decision-making.
- Company: Be part of a global private equity investor with a focus on innovation.
- Benefits: Enjoy opportunities for remote work and access to advanced tools.
- Why this job: Make an impact by enhancing analytical capabilities and driving data solutions.
- Qualifications: Bachelor's in a relevant field; experience in data analytics preferred.
- Other info: Strong teamwork and communication skills are essential for success.
The predicted salary is between 36000 - 60000 £ per year.
This is an excellent opportunity to join a specialist private equity investor with a global focus. As part of a high-performing team, you'll play a pivotal role in designing, developing and optimising data analytics and the internal infrastructure across portfolio systems and processes. In this role, you'll partner with global teams across finance, investor relations, and investments to deliver high-quality data solutions, enhance analytical capabilities, and support data-driven decision-making across the firm.
What the job involves:
- Build a strong understanding of the global portfolio, investments, and key datasets to support decision-making and insights across the business.
- Collaborate with teams to develop advanced analytical tools and reports focused on portfolio data, including cash flows, valuations, and operational metrics.
- Assist in maintaining and scaling key systems and infrastructure, such as portfolio monitoring platforms, deal flow and CRM systems, and proprietary tools like SQL Server and PowerBI models.
- Develop and optimise data pipelines to automate the collection, transformation, and loading of datasets, improving reporting workflows.
- Support the integration of AI capabilities with the data infrastructure to enhance analysis and insights.
Who we are looking for:
- Bachelor's degree in Computer Science, Data Science, Information Systems, Statistics, or related field.
- Experience in data analytics or similar role, preferably in financial services.
- Strong competency with PowerBI and automation tools.
- Strong competency with SQL and Python is preferred.
- Understanding of data modelling concepts and best practices.
- Strong problem-solving skills, communication skills and attention to detail.
- Advanced MS Excel proficiency.
- Strong team player and ability to build strong working relationships across the business.
Data Associate, Portfolio Analytics, Growth Equity Investor, London, UK - PER, Private Equity Recruitment employer: PER, Private Equity Recruitment
Contact Detail:
PER, Private Equity Recruitment Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Associate, Portfolio Analytics, Growth Equity Investor, London, UK - PER, Private Equity Recruitment
✨Tip Number 1
Familiarise yourself with the specific data analytics tools mentioned in the job description, particularly PowerBI and SQL. Consider creating a small project or case study that showcases your skills using these tools, as this can be a great conversation starter during interviews.
✨Tip Number 2
Network with professionals in the private equity sector, especially those who work in data analytics roles. Attend industry events or join relevant online forums to gain insights and potentially get referrals that could help you stand out in the application process.
✨Tip Number 3
Brush up on your understanding of financial services and how data analytics plays a role in decision-making within this field. Being able to discuss industry-specific challenges and solutions will demonstrate your genuine interest and knowledge during interviews.
✨Tip Number 4
Prepare for potential technical assessments by practising SQL queries and Python coding challenges. Many companies include practical tests in their interview process, so being well-prepared can give you a significant advantage.
We think you need these skills to ace Data Associate, Portfolio Analytics, Growth Equity Investor, London, UK - PER, Private Equity Recruitment
Some tips for your application 🫡
Understand the Role: Before applying, make sure you fully understand the responsibilities and requirements of the Data Associate position. Familiarise yourself with key terms like data analytics, SQL, PowerBI, and AI integration to tailor your application effectively.
Tailor Your CV: Customise your CV to highlight relevant experience in data analytics, particularly in financial services. Emphasise your skills in SQL, Python, and PowerBI, and include specific examples of projects or tasks that demonstrate your competency.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data analytics and your understanding of the private equity sector. Mention how your background aligns with the company's goals and how you can contribute to their data-driven decision-making.
Follow Application Instructions: When you're ready to apply, ensure you follow the application instructions on the company's website carefully. Double-check that all required documents are included and that your application is submitted before the deadline.
How to prepare for a job interview at PER, Private Equity Recruitment
✨Understand the Role
Before the interview, make sure you have a solid grasp of what the Data Associate role entails. Familiarise yourself with the key responsibilities such as data analytics, collaboration with global teams, and the use of tools like PowerBI and SQL. This will help you articulate how your skills align with their needs.
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SQL, Python, and PowerBI in detail. Consider bringing examples of past projects where you successfully used these tools to solve problems or improve processes. This will demonstrate your technical competency and relevance to the role.
✨Highlight Team Collaboration
Since the role involves working closely with various teams, be ready to share examples of how you've effectively collaborated in the past. Discuss any experiences where you built strong working relationships and contributed to team success, as this is crucial for the position.
✨Prepare Questions
At the end of the interview, you'll likely have the chance to ask questions. Prepare thoughtful questions about the company's data infrastructure, the team dynamics, or future projects. This shows your genuine interest in the role and helps you assess if it's the right fit for you.
