Data Scientist - Quant

Responsibilities

Lead and manage end-to-end quant / actuarial projects, ensuring successful delivery against timelines and objectives.

Build, validate, and deploy detection signals to capture market inefficiencies and arbitrage opportunities across markets.

Apply actuarial / quantitative principles to design robust models for risk, pricing, and performance monitoring.

Collaborate with cross-functional stakeholders including data and engineering teams to identify opportunities and implement data-driven solutions.

Continuously research, test, and implement new methodologies for predictive modelling and signal optimization.

Communicate findings, insights, and recommendations clearly to both technical and non-technical stakeholders.

Ensure documentation, reproducibility, and best practices are embedded into all modeling and project workflows.

The Successful Applicant

Qualification in Actuarial Science, Quantitative, Statistics, Mathematics, Data Science, or a related discipline.

Minimum 5 years of relevant working experience in actuarial, quant, or data-driven roles with a track record of project delivery.

Strong grounding in actuarial or quantitative concepts and principles.

Proficiency in Python programming, including experience with statistical and machine learning libraries.

Experience in predictive modeling, risk analytics, or market signal generation.

Familiarity with working on large, complex, or unconventional data sources.

Demonstrated ability to convert complex quantitative insights into actionable strategies.

Strong project management skills with ability to lead initiatives independently.

Excellent problem-solving, analytical thinking, and communication skills.

Ability to thrive in a fast-paced and evolving environment.

What's on Offer

Contract : 1 year

Completion Bonus - 1 month

Medical Benefits

Opportunity to work on cutting-edge projects in the Technology & Telecoms industry.

Collaborative and innovative work culture.

Access to professional development and learning opportunities.

If you are passionate about data and want to make an impact, we encourage you to apply for the Data Scientist role today!

Contact Charlene Fernandez Quote job ref JN- Phone number

#J-18808-Ljbffr