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Experience:

5 years required

Skills:

Data Analysis, Automation, Python

Job type:

Full-time

• Work with stakeholders throughout the organization to understand data needs, identify issues or opportunities for leveraging company data to propose solutions for support decision making to drive business solutions.
• Adopting new technology, techniques, and methods such as machine learning or statistical techniques to produce new solutions to problems.
• Conducts advanced data analysis and create the appropriate algorithm to solve analytics problems.
• Improve scalability, stability, accuracy, speed, and efficiency of existing data model.
• Collaborate with internal team and partner to scale up development to production.
• Maintain and fine tune existing analytic model in order to ensure model accuracy.
• Support the enhancement and accuracy of predictive automation capabilities based on valuable internal and external data and on established objectives for Machine Learning competencies.
• Apply algorithms to generate accurate predictions and resolve dataset issues as they arise.
• Be Project manager for Data project and manager project scope, timeline, and budget.
• Manage relationships with stakeholders and coordinate work between different parties as well as providing regular update.
• Control / manage / govern Level 2 support, identify, fix and configuration related problems.
• Keep maintaining/up to date of data modelling and training model etc.
• Run through Data flow diagram for model development.
• EDUCATION.
• Bachelor's degree or higher in computer science, statistics, or operations research or related technical discipline.
• EXPERIENCE.
• At least 5 years experience in a statistical and/or data science role optimization, data visualization, pattern recognition, cluster analysis and segmentation analysis, Expertise in advanced Analytica l techniques such as descriptive statistical modelling and algorithms, machine learning algorithms, optimization, data visualization, pattern recognition, cluster analysis and segmentation analysis.
• Expertise in advanced analytical techniques such as descriptive statistical modelling and algorithms, machine learning algorithms, optimization, data visualization, pattern recognition, cluster analysis and segmentation analysis.
• Experience using analytical tools and languages such as Python, R, SAS, Java, C, C++, C#, Matlab, SPSS IBM, Tableau, Qlikview, Rapid Miner, Apache, Pig, Spotfire, Micro S, SAP HANA, Oracle, or SOL-like languages.
• Experience working with large data sets, simulation/optimization and distributed computing tools (e.g., Map/Reduce, Hadoop, Hive, Spark).
• Experience developing and deploying machine learning model in production environment.
• Knowledge in oil and gas business processes is preferrable.
• OTHER REQUIREMENTS.

Experience:

1 year required

Skills:

Finance, Statistics, Python, English

Job type:

Full-time

• Manage/ Clean/ Prepare internal and external data (structured/ semi-structured/ unstructured data) for model development/ deployment/ monitoring, including the production of data quality and integrity report.
• Develop statistical/ expert/ hybrid models to be able to enhance the model when model deterioration is indicated using variety of data modeling techniques such as Logistic Regression/ Random Forest/ Gradient Boosting/ Non-Parametric Regression. Also, in case of using external consultants, be able to work closely with them across all m ...
• Generate prescriptive models to respond to interactive decision to optimize risks and rewards.
• Deploy credit risk models into Databricks platform, collection system and credit decision engine and maintain any model adjustment.
• Assist and work closely with related parties, e.g. business users, credit approval officers and relationship managers to ensure credit risk models are appropriate and efficient for business direction and support for new digital lending risk assessment and platform.
• Ensure all credit risk models are qualified to be used through model life cycle. Regularly perform model monitoring, model assessment and propose proactive action/ recommendation to improve the model.
• Assist and design for business opportunity to develop alternative credit score from partnership data.
• Collaborate with IT and data engineer to ensure data availability and quality from various sources (both on-premise/ cloud) to develop an efficient model.
• Qualifications Bachelor s or higher degree in Finance, Statistics, Mathematics, Economics, MIS, Engineer, Data scientist or any related fields.
• At least 1-2 year experiences credit risk analytics, credit risk modeling/ scoring in retail banking, consumer finance or any financial business.
• Strong knowledge and skill in machine learning, credit scoring, data analytics using R/ Python/ PySpark, MATLAB, SPSS, SAS, SQL or similar required.
• Analytical mindset with excellent critical thinking ability and data analytics skills.
• Excellent computer skills and programming tools.
• Good command in both written and spoken English.
• Good project management skills.
• Good team player with a positive attitude toward hard working and working under pressure.
• Experienced in credit risk modeling, model monitoring/ validation/ deployment/ maintenance preferred.
• Prior experience in Basel/ IFRS9, RAROC, Stress Test, Big Data, Data Mining, Digital leading, Fin-tech/ Start-up is a plus.
• We're committed to bringing passion and customer focus to the business. If you like wild growth and working with happy, enthusiastic over-achievers, you'll enjoy your career with us.