A Data Scientist is a specialist in doing deep dive analytics, with advanced level proficiency in data analytics by applying data science methodology, creating model algorithm (Mathematics or Statistical Model), data mining technique and storytelling delivery skills. He/she will perform data science practice for our Lending and Funding Business who will be instrumental and decisive in developing advanced analytics assets (but not limited to Credit Scoring, Propensity Model, Predictive Model, Recommender System, Risk Model Support, etc ) to support tribes’ objective key result and optimal business outcome.
- Minimum Bachelor's degree in Mathematics, Computer Science, Statistics, Engineering and related major is preferred
- Minimum 2 years experience as Data Scientist at Banking, Financial Services / FinTech Company
- Comfortable in scripting and strong in some of following programming languages: R, Java, Python with experience to apply Machine Learning frameworks and libraries (TensorFlow, Keras, Spark MLlib, Sklearn, pandas, etc)
- Familiar or has basic knowledge in one of data processing with statistic tools (SAS, SPSS, KNIME, Matlab, etc)
- Intermediate to advanced knowledge in some of data science methodologies either classic or black box including but not limited to classical regression, neural network, association rules, sequence analysis, classification, cluster analysis, gradient boost, text mining, etc.
- Solid analytical and problem-solving skills to interpret, derive and create data-driven insights
- Actively contribute in all aspects of ML model development: data wrangling, feature engineering, model selection / architecture, training, offline evaluation, plans A/B experimentation & roll out (production)
- Passionate and/or practicing in data technologies (Big Data, ETL, visualization, AI, ML, Deep Learning , etc) and care with details, numbers, and data’s quality.