Optasia is a fully-integrated B2B2X financial technology platform covering scoring, financial decisioning, disbursement & collection. We provide a versatile AI Platform powering financial inclusion, delivering responsible financing decision-making and driving a superior business model & strong customer experience with presence in 30 Countries anchored by 7 Regional Offices.
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.
Junior Quantitative Risk Data Scientists are significant contributors of Optasia's advanced risk management and revenue optimization and members of the Credit Portfolio Optimization team. The Credit Portfolio Optimization team members have experience with credit and profit scoring, the development, deployment and operation of credit risk models, and the day-to-day risk management of large portfolio of loans. They have the capability to (i) develop statistical and machine learning algorithms for credit issuance and risk evaluation, (ii) optimize revenue through risk management, (iii) conduct risk analytics, and (iv) operationalize models and analytics in the daily risk management activities of large portfolios of loans. Quantitative Risk Data Scientists are part of a large team of 25 people.
What you will do
- Perform in-depth risk analysis and optimization on microloans, accounting for 80% of the role.
- Develop predictive models, with a focus on statistical models and occasional machine learning applications.
- Deliver actionable insights on credit risk through advanced big data analytics.
- Identify and evaluate credit risk factors using computational methods on large datasets.
- Collaborate with cross-functional teams to support data-driven decision-making.
- Continuously refine risk models to optimize financial outcomes and minimize risk exposure.
What you will bring
- Bachelor’s degree in data science, Statistics, Mathematics, or a related field.
- Strong foundation in statistical modeling; experience with machine learning models is a plus.
- Proficiency in programming languages such as Python or R, with experience in big data analytics.
- Solid understanding of risk analytics and credit risk factors.
- Ability to handle and analyze large data sets to draw meaningful insights.
- Strong analytical and problem-solving skills.
Your key attributes
- Strong interpersonal and communication skills.
- Ability to hit tight deadlines and work under pressure and strict attention to detail.
- Excellent judgment and problem-solving skills.
- Experience in working with secure code development guidelines and coding practices (i.e. OWASP, NIST)
Why you should apply
What we offer:
💸 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.
