Senior Quantitative Risk Data Scientist, Fintech

Optasia is a fully enabled B2B2X financial technology platform covering scoring, financial decisioning, disbursement and collection. We are committed to enabling financial inclusion for all. We are changing the world our way .

We are seeking for enthusiastic professionals, with energy, who are results driven and have can-do attitude, who want to be part of a team of likeminded individuals who are delivering solutions in an innovative and exciting environment. Senior Quantitative Risk Data Scientist are significant contributors of Optasia's advanced algorithmic trading and portfolio optimization unit. As member of the Credit Portfolio Optimization team in Optasia, you will have an opportunity to combine the disciplines of risk management, research, and technology to operate trading strategies across multiple projects. You are expected to leverage your experience and knowledge in making critical decisions in real-time processes, while working closely with experienced traders, big-data, and machine-learning engineers to ensure optimal system performance.

What you will do

• Design and implement algorithmic solutions for revenues optimization though credit risk analysis.
• Deliver credit-risk insights through big data risk analytics.
• Development and implementation of portfolio risk assessment tools and procedures to monitor and manage credit risk.
• Conduct detailed risk analysis on microloans and other financial products, optimizing risk models to improve decision-making.
• Identify and evaluate credit risk factors using advanced computational methods on large datasets.
• Develop predictive models, including both statistical and machine learning approaches, to support risk management strategies.
• Collaborate closely with data scientists and data & machine learning engineers.
• Continuously refine and improve risk assessment methodologies to align with evolving market conditions.
• Mentor and guide junior and mid-level quants, fostering a collaborative and knowledge-sharing environment.
• Stay current with industry trends, new technologies, and evolving methodologies to ensure best-in-class risk management practices.

What you will bring

• Bachelor's or Master's degree in Data Science, Statistics, Finance, Mathematics, or a related field; a PhD is a plus.
• Extensive experience (6+years) in quantitative risk analysis, with a proven track record in the financial services industry.
• Strong expertise in algorithmic modeling and optimization techniques, with a focus on revenue and credit risk management.
• Advanced proficiency in statistical modeling and machine learning models.
• Strong coding skills in programming languages such as Python or R, with significant experience in big data risk analytics.
• Proven ability to develop and implement portfolio risk assessment tools and procedures.
• Excellent analytical, problem-solving, and decision-making skills.

Your key attributes

• Excellent judgment and problem-solving skills
• Self-motivated, self-directed, resourceful and in possession of a high level of personal initiative
• Communication skills
• Creative skills
• Experience in working with secure code development guidelines and coding practices (i.e. OWASP, NIST)

Why you should apply What we offer:

👟 Flexible remote working

💸 Competitive remuneration package

🏝 Extra day off on your birthday

💰 Performance-based bonus scheme

👩🏽‍⚕️ Comprehensive private healthcare insurance

📲 💻 All the tech gear you need to work smart

Optasia's Perks:

🎌 Be a part of a multicultural working environment

🎯 Meet a very unique and promising business and industry

🌌 🌠 Gain insights for tomorrow market's foreground

🎓 A solid career path within our working family is ready for you

📚 Continuous training and access to online training platforms

🥳 CSR activities and festive events within any possible occasion

🍜 Enjoy comfortable open space restaurant with varied meal options every day

🎾 🧘‍️ Wellbeing activities access such as free on-site yoga classes, plus available squash court on our premises

In accordance with applicable pay transparency requirements, the salary range for this position will be communicated to candidates before the first step of the selection process, enabling informed discussions regarding the role.