About UpPassUpPass provides a single API that unifies verification methods, fraud prevention technology, and reliable financial and identity data across Southeast Asia. Our mission is to empower Fintech and traditional financial institutions to overcome data fragmentation challenges. With our integrated API, we combine advanced KYC, fraud prevention technology, and verified data to make customer onboarding faster, more secure, and efficient.
About the RoleAs a Data Scientist at UpPass, you’ll play a critical role in driving data-driven insights and developing predictive models that fuel our SAAS and eKYC solutions. You’ll work alongside data engineers, software developers, and product teams to enhance data accuracy, streamline fraud prevention, and optimize identity verification systems. This role offers an opportunity to directly impact product innovation and contribute to solving real-world problems within the finance industry.
Key Responsibilities
- Data Analysis & Exploration: Gather, preprocess, and analyze large, complex datasets to uncover actionable insights, trends, and patterns that enhance our SAAS and eKYC offerings.
- Model Development: Design, implement, and evaluate machine learning algorithms and statistical models for fraud detection, identity verification, and customer behavior analysis.
- Data Visualization: Create impactful data visualizations and dashboards to effectively communicate findings and data-driven insights to cross-functional teams.
- Model Optimization & Evaluation: Perform rigorous testing, validation, and refinement of models to ensure optimal performance and accuracy, adapting models as necessary based on evolving data.
- Cross-functional Collaboration: Work with engineers, data engineers, and product managers to seamlessly integrate data science solutions into our product ecosystem.
- Research & Innovation: Stay current with industry advancements in machine learning, data science, and AI, bringing new ideas and approaches to our projects.
- Documentation & Reporting: Maintain thorough documentation of data workflows, model development, and outcomes for transparency and reproducibility.
Qualifications
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.
- Proven experience in data analysis, statistical modeling, and machine learning techniques.
- Proficiency in Python, R, and SQL for data manipulation and analysis.
- Experience with data visualization tools such as Tableau, Power BI, or similar platforms.
- Strong analytical and problem-solving skills with attention to detail.
- Knowledge of cloud platforms (AWS, GCP, or Azure) is a plus.
- Excellent communication skills and ability to convey complex information to both technical and non-technical audiences.
- A passion for data and a strong drive to create data-driven solutions.
