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- Tasks: Analyse data to support investment decisions and portfolio management for high-growth startups.
- Company: Join a leading venture capital firm focused on digital and sustainable innovations.
- Benefits: Enjoy flexible working, private medical insurance, and 25 days holiday plus wellbeing days.
- Why this job: Be at the forefront of innovation, collaborating with startups and industry experts.
- Qualifications: Experience in data analysis, strong skills in Python and SQL, and knowledge of financial metrics required.
- Other info: Opportunity to work overseas for up to a month per year.
The predicted salary is between 29000 - 37000 £ per year.
Are you passionate about data-driven decision-making and eager to influence investment strategies? Join a leading venture capital firm that backs early-stage startups shaping a digital and sustainable built world.
My client is seeking a Portfolio Data Analyst to support investment decision-making and portfolio management by analysing data from high-growth startups. You’ll work closely with investors and founders to provide insights that drive strategic growth.
Your Responsibilities:
- Data Collection & Management: Maintain structured data processes, ensuring accuracy and consistency in financial and operational data from portfolio companies.
- Financial Modelling across portfolio accounts.
- Performance Tracking: Develop dashboards and reports to monitor key performance indicators (KPIs), such as revenue growth, burn rate, and valuation changes.
- Process Automation: Implement data pipelines and automation strategies to enhance reporting and analysis.
- Data Insights & Predictive Analytics: Build models to forecast startup performance, detect early warning signals, and assess risks.
- Investor Reporting: Assist in preparing fund updates, investor reports, and presentations.
- Collaboration: Work closely with VC partners, portfolio founders, and stakeholders to align on key metrics.
- Follow-on Investment Analysis: Support due diligence by analysing industry benchmarks, financial statements, and market trends.
You Will Need:
- Experience in data science, financial analytics, or investment-related data analysis (VC, PE, banking, consulting, or startups).
- Strong proficiency in Python, SQL, and data visualisation tools (Tableau, Power BI, Looker).
- Solid understanding of statistical techniques and an ability to extract insights from complex datasets.
- Familiarity with venture capital metrics (ARR, CAC, LTV, burn rate, etc.) and financial modelling.
- Strong communication skills, with the ability to present findings to both technical and non-technical audiences.
It’s a Bonus If You Have:
- Experience working in a VC environment or with portfolio management tools (Affinity, Vestberry, Carta, PitchBook).
- Knowledge of machine learning techniques and their commercial applications.
The Benefits:
- Work at the forefront of innovation, collaborating with high-growth startups.
- Competitive salary and benefits, including private medical insurance and flexible working.
- Access to mentoring, workshops, and industry-leading experts.
- 25 days’ holiday plus bank holidays, with additional wellbeing days.
- Opportunity to work overseas for up to a month per year.
If you’re excited about using data to drive investment decisions, apply now to join a team shaping the future of the digital and sustainable built world!
Financial Data Analyst employer: Intellect Group
Contact Detail:
Intellect Group Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Financial Data Analyst
✨Tip Number 1
Familiarise yourself with the specific financial metrics mentioned in the job description, such as ARR, CAC, and LTV. Understanding these terms will not only help you in interviews but also demonstrate your knowledge of the venture capital landscape.
✨Tip Number 2
Showcase your technical skills by preparing a small project or portfolio that highlights your proficiency in Python, SQL, and data visualisation tools like Tableau or Power BI. This practical demonstration can set you apart from other candidates.
✨Tip Number 3
Network with professionals in the venture capital space through platforms like LinkedIn. Engaging with industry experts can provide insights into the role and may even lead to referrals, increasing your chances of landing an interview.
✨Tip Number 4
Prepare to discuss how you've used data to influence decision-making in past roles. Be ready to share specific examples that highlight your analytical skills and ability to communicate findings effectively to both technical and non-technical audiences.
We think you need these skills to ace Financial Data Analyst
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data science and financial analytics. Emphasise your proficiency in Python, SQL, and any data visualisation tools you've used, as these are crucial for the role.
Craft a Compelling Cover Letter: In your cover letter, express your passion for data-driven decision-making and how it aligns with the company's mission. Mention specific examples of how you've used data to influence investment strategies or improve performance tracking.
Showcase Relevant Skills: Clearly outline your understanding of venture capital metrics and financial modelling in your application. Highlight any experience you have with process automation and predictive analytics, as these are key responsibilities of the role.
Prepare for Interviews: If selected for an interview, be ready to discuss your previous projects involving data analysis and financial modelling. Prepare to explain complex datasets in simple terms, showcasing your strong communication skills.
How to prepare for a job interview at Intellect Group
✨Showcase Your Data Skills
Be prepared to discuss your experience with data analysis tools like Python and SQL. Highlight specific projects where you've successfully used these skills to drive insights or improve processes.
✨Understand Venture Capital Metrics
Familiarise yourself with key venture capital metrics such as ARR, CAC, and burn rate. Being able to discuss these concepts confidently will demonstrate your understanding of the industry and its financial dynamics.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Prepare examples of how you've tackled challenges in data analysis or financial modelling, particularly in a fast-paced environment like a startup.
✨Communicate Clearly
Practice explaining complex data insights in simple terms. The ability to present findings to both technical and non-technical audiences is crucial, so ensure you can articulate your thoughts clearly and effectively.
