Join the Pioneer Crypto Brand in the Philippines!
Coins is the most established crypto brand in The Philippines and has gained the trust of more than 18 million users. Through the easy-to-use mobile app, users can buy and sell a variety of different cryptocurrencies and access a wide range of financial services.
Coins is fully regulated by the Bangko Sentral ng Pilipinas (BSP) and is the first ever crypto-based company in Asia to hold both Virtual Currency and Electronic Money Issuer licenses from a central bank.
What you'll do
- End-to-end delivery of data driven product incubation, working with Product Management to gather and prepare data/features, to analyze data with programming/statistical languages (e.g. R, Python) and generate insights, to choose and deploy Machine Learning models, solving for the business opportunities identified.
- Interact cross-functionally, making business recommendations (e.g., cost-benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
- Conduct analysis that includes data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Process, cleanse, and verify the integrity of data used for analysis.
- Data mine for important information and insights and present results in a clear manner and conciseSolve difficult, non-routine analysis problems, applying advanced analytical methods as needed.
- Build and prototype analysis pipelines iteratively to provide insights at scale.
- Select features, build and optimize classifiers with machine learning techniques.
- Develop comprehensive knowledge of Coins data structures and metrics, advocating for changes where needed for product development.
- Understands development and quality standards and ensures strict adherence to themWrite model documentation clearly and concisely and support findings with reasonable foundations.
- Sharing best practices and case studies, helping to lift the overall literacy.
- Develop collaborations with product management and engineering team.
- Degree in a quantitative discipline (e.g., Statistics, Operations Research, Bioinformatics, Economics, Computational Biology, Computer Science, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience.
- 3-5 years of experience in the analytics or related fieldStrong expertise and hands-on experience in statistical analysis and modeling, machine learning models, data visualization.
- Demonstrated experience in working with large, complex data sets.
- Fluent in SQL, R, and PythonFamiliarity with BI Tools such as Qlik, Tableau and Metabase.
- Intermediate knowledge of big data technologies such as (Kafka/Flink/Spark etc).
- Demonstrated leadership and self-direction.
- Willingness to teach others and learn new techniques.
- Experience with agile development methodology.
- Effective written and verbal communication skills.
- An advanced degree in a quantitative discipline
- Team lead experience, with a focus on building and leading (small) teams of data scientists.
- Specialized knowledge in time series analysis, deep learning, NLP, and graph analytics.
- Experience in deploying machine learning model as cloud native application or container application.
- Demonstrated expertise with statistical data analysis such as linear models, multivariate analysis, stochastic models, sampling methods.
Join the Coins Team Now!
Meaningful Collaborations - The successful candidate will work cross-functionally with other relevant teams to carry out implementations that will improve and create an impact on customer experience.
Scalable Growth - Be part of a fast-growing organization with the vision to expand its territories outside APAC which will provide opportunities for career advancement.
A Space For Bright Ideas - Let your bright ideas be converted into meaningful changes! Coins culture welcomes new ideas backed up by data to create an impact.
This job is already closed and no longer accepting applicants, sorry.