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. The Data Scientist joins the AI department within the Data & Risk team, which is responsible for Data Management and Credit Risk optimization. The core responsibilities of the role are to contribute to the research and development of AI models and methods, and to support, through model-driven initiatives, core risk and business use cases across Optasia’s products. The successful candidate must be results-oriented, self-motivated and able to operate effectively in dynamic and fast-paced environments. The role involves frequent collaboration with Credit Traders, Quantitative Risk Data Scientists and Business stakeholders.

What you will do

• Design, develop and implement statistical and machine learning models that support risk management, pricing and data-driven decisioning.
• Build and maintain models that operate on large-scale datasets and support core product and risk decisions.
• Perform in-depth analysis on financial products to improve model performance and business outcomes.
• Contribute to the development of model monitoring, validation and performance tracking frameworks.
• Identify and evaluate key model drivers and assumptions using large and complex datasets.
• Collaborate closely with data scientists, quantitative risk experts and data & machine learning infrastructure engineers within the Data & Risk department.
• Monitor model performance and support continuous optimization and recalibration.

  What you will bring

• Bachelor’s or Master’s degree in Data Science, Statistics, Mathematics, Finance, Computer Science or a related quantitative field.
• 2–4 years of experience in Data Science, Machine Learning or applied analytics.
• Solid understanding of statistical modeling and machine learning techniques.
• Strong programming skills in Python and SQL.
• Experience working with large datasets and production-oriented data pipelines.
• Strong analytical and problem-solving skills with attention to detail.
• Ability to translate business and risk problems into AI-driven solutions.
• Strong communication skills and ability to work in collaborative, cross-functional teams.
• Results-driven with strong ownership mentality.
• Curious, proactive and eager to learn.
• Comfortable working in fast-paced, dynamic environments.
• Strong sense of responsibility and analytical rigor.

Why you should apply
What we offer:
👟 Flexible hybrid 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

Optasia’s Values 🌟

#1 Drive to Thrive: Fully dedicated to evolving. We welcome all challenges and learning opportunities.
#2 Customer-First Mindset: We go above and beyond to meet our partners’ and clients’ expectations.
#3 Bridge the Gap: Knowledge is shared, information is exchanged and every opinion counts.
#4 Go-Getter Spirit: We are results oriented. We identify any shortcomings that hold us back and step up to do what’s needed.
#5 Together we will do it: We are committed to supporting one another and to understanding and respecting different perspectives, as we aim to reach our common goals.