AI Summary
Join our team as a Machine Learning Engineer to accelerate the development of robust, high-performing ML solutions. Collaborate with cross-functional teams to drive measurable business impact through better models. Evaluate model performance and business impact, and iterate for continuous improvement.
Key Highlights
Own the end-to-end lifecycle of ML models
Collaborate with cross-functional teams
Evaluate model performance and business impact
Key Responsibilities
Own the end-to-end lifecycle of ML models: from EDA, feature generation, and hypothesis testing to production deployment and monitoring
Collaborate with cross-functional teams - especially Collection and Product - to identify high-leverage modeling opportunities
Evaluate model performance and business impact, and iterate for continuous improvement
Technical Skills Required
Benefits & Perks
Relocation package provided
Preference will be given to candidates open to relocating to Manila
Job Description
We’re looking for a curious and impact-driven Machine Learning Engineer to join our team and accelerate the development of robust, high-performing ML solutions across key business areas - including credit scoring, collection, antifraud, sales and other.
This role combines hands-on development with strategic input, offering a chance to work on high-stakes, high-visibility projects from day one, collaborating with multiple departments and stakeholders to drive measurable business impact through better models
Preference will be given to candidates open to relocating to Manila
Your Future Tasks
- Own the end-to-end lifecycle of ML models: from EDA, feature generation, and hypothesis testing to production deployment and monitoring
- Collaborate with cross-functional teams - especially Collection and Product - to identify high-leverage modeling opportunities
- Evaluate model performance and business impact, and iterate for continuous improvement
- Explore and integrate new data sources (internal and external), identifying additional predictive signals
- Work with production systems to ensure models are scalable, observable, and maintainable
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- 2+ years of experience as a Machine Learning Engineer or Data Scientist, ideally in fintech or fast-paced product environments
- Solid foundation in classical ML techniques and fluency in core libraries such as Pandas, Scikit-learn, NumPy, SciPy, Matplotlib, Seaborn, Statsmodels, XGBoost/LightGBM/CatBoost etc
- Strong proficiency in Python and SQL, experience with version control
- Strong sense of ownership and accountability
- Experience working with AWS (or other cloud environments) is a plus
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