About the Department
We are seeking a Junior Quantitative Trader based in Edinburgh, to support trading activities across equities, FX, and cash instruments for UK markets. This is a hybrid role that is execution and workflow oriented, while also having a mandate on streamlining execution and trading operations with quantitative and analytics approaches.
This role is ideal for someone with strong quantitative and technical skills who is interested in markets, execution, and real-world trading outcomes, rather than academic model development.
The successful candidate will work closely with traders to:
- Support day-to-day trading and execution
- Analyse and monitor algorithmic trading performance
- Improve execution and trading workflows by developing a systematic approach integrating internal systems, vendors and various data sources
How You Will Add Value
Trading & Execution Support
- Assist traders in executing cash equity and FX trades, with a focus on best execution
- Build a deep understanding of market structure and trading venues across markets
- Monitor market conditions, liquidity, and execution quality across asset classes
- Support daily cash and FX management activities as needed
Algorithm & Performance Analysis
- Analyse performance of execution algorithms and trading strategies
- Help identify drivers of slippage, costs, and performance variance
- Produce regular execution and performance reporting for traders and management
Workflow & Data Engineering
- Work closely with global quantitative execution team to improve trading workflows by utilizing internal systems, vendor data, and market data
- Automate recurring analyses and reporting to improve desk efficiency
- Work with large trade-oriented datasets to visualize and extract actionable insights to systematically improve executions
- Partner with technology, data, and trading teams to streamline processes
Risk & Controls
- Support trade monitoring, reconciliations, and exception handling
- Assist with adherence to internal risk, compliance, and control frameworks
What Will Help You Be Successful in This Role
Experience, Education & Certifications
- Degree in finance, economics, mathematics, engineering, computer science, or related quantitative or technical fields with relevant quant experience.
- Strong interest in financial markets and trading
- Proficiency in Python (or similar language) for data analysis and automation
- Comfort working with large datasets and multiple data sources
- Strong analytical and problem-solving skills
- High attention to detail and ability to work in a fast-paced trading environment
Preferred Qualifications
- Exposure to Asset Management, with Trading knowledge preferred but not essential
- Experience working with SQL, APIs, or market data vendors
- Experience in Machine Learning and AI models; Power Automate and Cloud database
- Internship or prior experience in Asset Management and/or Trading preferred
Franklin Templeton is an Equal Opportunity Employer. We are committed to providing equal employment opportunities to all applicants and existing employees, and we evaluate qualified applicants without regard to ancestry, age, color, disability, genetic information, gender, gender identity, or gender expression, marital status, medical condition, military or veteran status, national origin, race, religion, sex, sexual orientation, and any other basis protected by federal, state, or local law, ordinance, or regulation.
As part of our commitment to fostering a diverse and inclusive work environment, we welcome applicants with flexible working arrangements in their current roles or those seeking a flexible working pattern. We encourage you to communicate any preferences for flexible working so that we can consider this during our hiring process. Additionally, returners – individuals who have taken a break from work – are also encouraged to explore our job opportunities.
As a registered UK Disability Confident Committed Employer, we encourage you to disclose if you consider yourself to have a disability as part of your application.
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