Define data sources and requirements, design and implement processes and models for complex, large-scale datasets used for predictive modelling, data mining, and research purposes.
Provide critical thinking to look at numbers, trends, and data and come to correct conclusions based on the findings.
Analyst data (structured and un-structured) and to recommend appropriate Machine-Learning (ML) solutions for business objectives
Develop and support predictive analytics models using R and/or Python
Work with the deployment teams to translate models into technical solutions for BAU
Incorporate machine learning and results from experiments into refined models for predictive risk management.
Identify opportunity and conduct R&D to improve efficiency & effectiveness of business process using ML model across variety of fields such as risk, marketing, collection, customer service, underwriting; by using our vast amount and unique set of data
Present key findings to senior management and/or other stakeholders with actionable recommendations.
4+ years of industry experience in working at financial domain for a consumer-facing company
Experience building robust end-to-end predictive models using the latest Machine Learning techniques and methodologies
Proficiency in Python or R. Exposure to RDBMS (i.e. MySQL, PostgreSQL) and No-SQL platforms (i.e. S3)
Proven experience leading data-driven projects from definition to execution: defining metrics, experiment design, communicating actionable insights.
Experience with alternate data to evaluate credit risk
Experience in building state of the art Computer Vision or NLP models