At a Glance
- Tasks: Dive deep into data to extract market insights and develop predictive models.
- Company: Join Eka Finance, a leader in innovative financial analytics.
- Benefits: Enjoy remote work flexibility, competitive pay, and opportunities for professional growth.
- Other info: Collaborate with a dynamic team in a fully remote environment.
- Why this job: Make an impact by transforming complex data into actionable investment insights.
- Qualifications: Master’s or PhD in a quantitative field and strong Python skills required.
The predicted salary is between 60000 - 80000 € per year.
We are seeking a Quantitative Analyst to join our research team in a fully remote capacity. The team focuses on extracting market-relevant insights from alternative data, sentiment indicators, and rigorous quantitative analysis. This role is research-intensive and hands-on, involving signal development, model validation, and systematic evaluation of investment ideas across multiple asset classes. The ideal candidate is intellectually curious, technically strong, and motivated to translate complex datasets into robust, decision-ready insights while working in a distributed environment.
Core Responsibilities
- Conduct in-depth quantitative analysis of hedge fund performance, including return decomposition, risk metrics, and factor exposures.
- Develop and maintain proprietary analytical frameworks to assess manager skill, performance persistence, and style consistency across market regimes.
- Perform attribution and factor-based analysis to evaluate alignment between managers’ stated investment processes and realised results.
- Build and maintain factor and risk models to analyse correlations, beta exposures, and portfolio overlap across the manager universe.
- Analyse portfolio-level characteristics such as liquidity profiles, concentration, leverage, and counterparty exposures.
- Provide quantitative support to the CIO for manager selection, due diligence, and ongoing monitoring.
- Produce high-quality analytical materials for the investment committee, translating complex quantitative results into actionable insights.
Broader Asset Class & Data Research
- Source, clean, and normalise alternative datasets, including sentiment, social media, and ESG data.
- Develop predictive models and signals using time-series analysis, statistical techniques, and machine-learning methods.
- Design and maintain robust backtesting frameworks, incorporating transaction costs and market impact.
- Build and monitor risk models and conduct stress testing across different market scenarios.
- Document research methodologies and clearly present findings to internal stakeholders.
Required Experience & Skills
- Master’s or PhD in Finance, Economics, Mathematics, Statistics, Computer Science, Engineering, or a related quantitative discipline.
- Experience in quantitative research, data science, or analytics within financial markets (buy-side or sell-side).
- Proven ability to design, implement, and validate quantitative models using real-world market data.
- Strong proficiency in Python for research and modelling (pandas, numpy, scipy, statsmodels, scikit-learn).
- Experience working with large datasets and databases (SQL and/or NoSQL).
- Solid foundation in statistics, including regression, time-series analysis, factor modelling, and signal processing.
- Good understanding of financial market structure, pricing dynamics, and liquidity.
- Ability to work effectively in a remote, distributed research environment, managing priorities and collaborating across time zones.
Desirable Skills & Experience
- Experience working with sentiment, news, social media, or other alternative datasets.
- Background in machine learning, NLP, or other advanced modelling techniques applied to financial data.
- Familiarity with cloud-based data and research environments (AWS, GCP, Azure).
- Exposure to portfolio construction, risk analytics, or systematic factor-based strategies.
Quantitative Analyst – Research & Analytics (Remote) - Eka Finance in London employer: Jobs via eFinancialCareers
Eka Finance is an exceptional employer for Quantitative Analysts, offering a fully remote work environment that fosters intellectual curiosity and technical excellence. With a strong emphasis on employee growth, the company provides opportunities to engage in cutting-edge research and analytics, while promoting a collaborative culture that values diverse perspectives and innovative thinking. Employees benefit from access to advanced tools and resources, enabling them to translate complex datasets into impactful insights within the dynamic landscape of financial markets.
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Analyst – Research & Analytics (Remote) - Eka Finance in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the finance and analytics space on LinkedIn. Join relevant groups, participate in discussions, and don’t hesitate to ask for informational interviews. You never know who might have a lead on your dream job!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your quantitative analysis projects. Use GitHub or a personal website to display your work with Python, data models, and any predictive analytics you've done. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Brush up on your technical skills and be ready to discuss your past projects in detail. Practice common quantitative analyst interview questions and think about how you can relate your experiences to the role at Eka Finance.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your experience with alternative datasets and quantitative research, and let us know why you’re excited about this remote opportunity.
We think you need these skills to ace Quantitative Analyst – Research & Analytics (Remote) - Eka Finance in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your quantitative analysis experience and any relevant projects you've worked on. We want to see how you can bring value to our research team!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about quantitative analysis and how your background aligns with our needs. Be sure to mention any specific tools or methodologies you’ve used that relate to the role.
Showcase Your Technical Skills:Since this role requires strong technical abilities, make sure to highlight your proficiency in Python and any experience with data science tools. We love seeing examples of how you've applied these skills in real-world scenarios, so don’t hold back!
Apply Through Our Website:We encourage you to apply directly through our website for a smoother application process. It helps us keep track of your application and ensures you’re considered for the role. Plus, it’s super easy to do!
How to prepare for a job interview at Jobs via eFinancialCareers
✨Know Your Numbers
Brush up on your quantitative analysis skills and be ready to discuss specific models or frameworks you've developed. Be prepared to explain how you approached a complex dataset and the insights you derived from it.
✨Showcase Your Technical Skills
Make sure you can demonstrate your proficiency in Python and any relevant libraries like pandas or scikit-learn. Consider preparing a small project or example that highlights your ability to manipulate data and build predictive models.
✨Understand the Market Landscape
Familiarise yourself with current trends in financial markets, especially regarding alternative data and sentiment analysis. Being able to discuss recent developments will show your intellectual curiosity and passion for the field.
✨Communicate Clearly
Since this role involves translating complex quantitative results into actionable insights, practice explaining your findings in simple terms. Use examples from your past work to illustrate how you’ve effectively communicated complex ideas to stakeholders.
