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Quantitative Analyst
About Tangible
Tangible is a fast-growing, tech-driven platform providing liquidity solutions to LPs and GPs in the private-markets secondaries space. By combining deep sector expertise with modern infrastructure, we unlock liquidity across private equity, private credit, and real assets, transforming the industry and enabling investors to move faster and smarter.
About the Role
We are looking for an experienced Quantitative Analyst to join our growing team. In this pivotal role, you will act as a bridge between our analyst team and tech team, helping to integrate financial modeling capabilities onto our platform. You will also play a crucial part in launching a new project aimed at automating data extraction and analysis processes, empowering investment teams to focus on high-value analytical tasks.
This role is open globally to full-time contractors who can work standard Central European Time (CET) hours.
Tasks
Bridge Between Research, Product, and Engineering
- Act as the bridge between research, product, and engineering teams.
- Grasp the research-to-production lifecycle of how research becomes a prototype, and a prototype becomes a robust, production-grade system.
- Ensure that financial models and research outputs are accurately and effectively implemented within the platform.
Financial Modeling Integration
- Collaborate with the tech team to integrate advanced financial modeling capabilities into our platform.
- Translate complex financial models into actionable technical requirements for developers.
- Ensure that financial models are accurately and effectively implemented within the platform.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Project Leadership for New Tool Development
- Lead the initiative to develop a tool that automates data extraction and analysis processes for investment teams.
- Work closely with product and tech teams to define project scope, objectives, and deliverables.
- Provide insights on client needs to guide the development of features that add value for investment teams.
Ownership of the Product Development Lifecycle
- Operate across the product development lifecycle, where requirements originate with product, flow to research or engineering, timelines and a roadmap take shape, milestones are hit, and the product ships.
Cross-Team Collaboration
- Act as a liaison between the analyst team and tech team to facilitate effective communication and project execution.
- Collaborate with analytics and management teams to understand data needs and deliver actionable insights.
Reporting and Communication
- Prepare comprehensive reports to document findings in a professional and concise manner.
- Apply critical thinking to interpret data and clearly communicate implications to stakeholders.


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Requirements
- A strong research-to-product mindset: someone who wants to build tools and models for an investment product and has solved problems where the data is sparse or unreliable.
- Minimum MSc, PhD preferred, in a data-intensive science (Physics, Maths, Statistics, Engineering, Machine Learning, or a related discipline).
- Exposure to financial modelling, whether through professional work, academic study, or personal projects.
- Strong knowledge of statistical methods and data analysis techniques, paired with the ability to solve problems creatively.
- Tech stack: strong Python, good level with Bash and the command line, basic knowledge of JavaScript, fluency in Excel and DuckDB, and Git for version control.
- Excellent critical thinking skills, with the ability to draw actionable insights from data and communicate implications clearly.
- Strong written communication skills, with the ability to document findings professionally and concisely.
- Proven collaboration skills, with experience working effectively in cross-functional and remote/distributed teams with tight deadlines.
- Thrives in a fast-moving startup environment - flexible, proactive, and self-directed.
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