Roles & Responsibilities:
* Own end-to-end data science projects from the exploration phase to implementation in production to post-production monitoring
* Improve our infrastructure for training and deploying machine learning models, both batch and real-time
* Consolidate datasets comprising range of structured and unstructured data; get involved in ETL process if required
* Develop contextual domain knowledge around the problem by interacting with a range of stakeholders
* Build explanatory as well as predictive models for fraud detection & credit risk assessment
Skills & Qualifications:
* Strong proficiencies in various statistical and non-statistical approaches to machine learning
* 3+ years experience dealing with large real-world datasets, running an iterative ML pipeline in a production environment
* Substantial experience building mission-critical systems
* You should be technical, and be able to quickly pick up new engineering skills needed
* You have a strong framework to differentiate a good model from the bad
* You are curious to uncover the story behind the data
* Domain experience in credit and risk is highly preferred.
To be successful in this role, you would need to be highly analytical, have the ability to synthesise information well from disparate sources, and be extremely curious about the problem! In return, you would get to work on proprietary, hard to reproduce, rich financial and behavioral datasets and ship models that will be a force multiplier for NIRA and its customers.