Data Scientist
Data Scientist
About the job
We are looking for a self-motivated, eager-to-learn individual interested in identifying and solving business problems. This individual utilizes their data analytics and machine learning skills to turn available data into a solution to support business teams.
Job Responsibilities
Build, validate, maintain, and monitor credit risk models (application / behavior / collection) and marketing models (propensity / churn / etc.).
Analyze company’s data to optimize customer loan-to-value ratio (LTV), risk-based pricing, and risk policies based on risk factors and product direction.
Collaborate with key stakeholders to identify and translate business questions into analytical problems and recommend solutions to improve current ways of working.
Build and maintain the customer feature layer that supports analytics and machine learning models, ensuring features are documented, reusable, and consistent across the company’s operations.
Analyze data provided by partners / third parties to improve current models and business operations.
Qualifications
Required
Bachelor's or Master's degree in Data Science, Statistics, Economics, Computer Science, Computer Engineering, Information Technology, or a related field.
Proficiency in SQL and Python's data stack — pandas, numpy, scikit-learn.
Understanding of core statistical concepts and the model development lifecycle, including feature engineering, evaluation metrics, and common failure modes such as overfitting and data leakage.
Ability to explain analytical results, assumptions, and limitations to non-technical stakeholders.
Nice to have
Familiarity with version control (Git) and basic MLOps practices.
Experience with Google Cloud Platform and its data stack, or in financial services.
AI Engineer
About the job
We are looking for a self-motivated, eager-to-learn individual interested in building AI solutions that solve business problems. Working within the data science team, this individual applies their analytical, machine learning, and engineering skills to turn unstructured data into deployed, reliable services that support and improve business teams' work.
Job Responsibilities
Build, maintain, and improve AI solutions for unstructured data (document classification and extraction, voice and call transcript analytics, and text understanding).
Work with business users to understand their processes in depth, define what the AI solution should do, and design the prompts and pipeline logic that deliver it.
Build LLM-based components (retrieval, prompting, and structured output) and define evaluation criteria to measure and track output quality.
Deliver the analytical output of AI solutions to the business teams that use them to suggest improvements to their operations.
Own the deployment path for AI solutions and for models handed over by the data science team, and working with IT on real-time services.
Qualifications
Required
Bachelor's or Master's degree in Computer Science, Computer Engineering, Data Science, Information Technology, or a related field.
Proficiency in Python and SQL, with hands-on experience applying AI methods to unstructured data — text classification, embeddings and retrieval, speech-to-text, and LLM prompting and evaluation.
Ability to break down a business process into a well-defined AI problem, and to explain technical trade-offs and solution limitations to non-technical stakeholders.
Nice to have
Experience with Thai-language text or speech data, and with the practical limitations of general-purpose models on Thai.
Understanding of deploying and operating production workloads on Google Cloud Platform.