Senior Trading Risk & Fraud Analyst

GRS Recruitment; Nicosia; In loco; EUR 50.000 - 70.000; Tempo pieno

Descrizione del lavoro

A leading international trading firm is seeking a Senior Trading Risk & Fraud Analyst in Nicosia, Sicily. This pivotal role involves leveraging advanced analytics to mitigate trading risks, mentoring junior analysts, and enhancing fraud detection methodologies. Ideal for experienced professionals passionate about risk management in a data-driven environment.

Competenze

• Minimum 4 years of experience in trading risk or fraud detection.
• Strong understanding of financial markets and trading platforms.
• Experience with AI-driven technologies in risk management.

Mansioni

• Analyse trading data to detect anomalies and patterns.
• Lead investigations into suspicious trading behaviours.
• Collaborate with internal departments to enhance risk detection.

Conoscenze

Data analytics

Risk management

Fraud detection

Communication

Decision-making

Formazione

Degree in Finance, IT, Data Analytics, Business

Strumenti

Python

R

SQL

Descrizione del lavoro

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Senior Trading Risk & Fraud Analyst, Nicosia, Sicily

Client: GRS Recruitment

Location:

Job Category: Other

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EU work permit required: Yes

Job Reference:

fa49eb1ee887

Job Views:

4

Posted:

28.06.2025

Expiry Date:

12.08.2025

Job Description:

GRS Recruitment is working closely with a leading international trading firm with a significant presence in Cyprus, currently seeking to recruit a Senior Trading Risk & Fraud Analyst to join their expanding Nicosia-based team. This opportunity is with a highly innovative and data-driven organisation at the forefront of trading technology. The successful candidate will play a pivotal role in identifying and mitigating risks across trading operations, leveraging advanced analytics, AI tools, and market expertise to ensure the integrity of the trading environment. This is a high-impact role ideal for professionals who thrive in fast-paced, high-responsibility environments and are passionate about enhancing risk frameworks and mentoring junior team members.

MAIN DUTIES AND RESPONSIBILITIES

1. Analyse complex trading data to detect anomalies, patterns, and potential threats within trading activity.
2. Lead investigations into suspicious or high-risk trading behaviours, working to strengthen internal controls and risk strategies.
3. Monitor key trading risks such as exposure risk, concentration risk, systemic vulnerabilities, and product-related risks.
4. Utilise AI-powered analytics and machine learning tools to enhance fraud detection and proactively identify emerging risks.
5. Collaborate with internal departments including trading, compliance, and IT to develop and enhance risk detection methodologies and early warning systems.
6. Mentor junior analysts, promoting a proactive and analytical risk culture within the team.
7. Continuously review and refine tools and processes to improve real-time monitoring of trading operations.

CANDIDATE PROFILE

1. A degree in Finance, IT, Data Analytics, Business or a related field.
2. Minimum 4 years of experience in a relevant role, with at least 2–3 years specifically in trading risk, fraud detection, or monitoring within the financial or online trading industry.
3. Strong understanding of financial markets, trading platforms, and derivative products.
4. Experience working with platforms such as MT5 Manager/Administrator or cBroker is considered an advantage.
5. Proficiency in data analytics tools and techniques, with knowledge of Python, R, SQL, or machine learning models.
6. Excellent decision-making skills under pressure, with a structured and data-driven approach.
7. Strong communication skills and ability to present complex findings clearly to both technical and non-technical audiences.
8. Prior experience in leading small projects or mentoring junior staff is highly desirable.
9. An interest in, or experience with, AI-driven technologies in the context of fraud or risk management.

Due to the high volume of applications, only shortlisted candidates will be responded to.