- 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.
Requirements:
- 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.
Added advantage
- Experience with alternate data to evaluate credit risk
- Experience in building state of the art Computer Vision or NLP models
Please send your detailed resume in MS Word format to : [email protected]
stating your notice period / earliest available commencement date, current & expected salaries