Experience in:
- Demonstrated track record of having applied data science methods to multiple retail asset products
- End to end experience from data extraction to modelling and its validation
- Knowledge of Mortgage business would be a big plus
- Preferably more than 4-5 yrs of experience in Analytics / Data science vertical with proven credentials
- Experience in data mining, Knowledge of R, SQL and Python; familiarity with Java or Scala would be a plus
- Experience with data visualization tools
- Good applied statistics skills, such as distributions, statistical testing, regression, etc.
- Experience using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)
- Is hands-on currently and proficient with SAS and Python coding
- Familiarity with developing models using semi structured as well as unstructured data.
- Past experience of Credit/underwriting/sales/collections would be an additional asset.
Job description
- Analyze large amounts of data/ information to discover trends and patterns for the retail asset products
- Evangelize the use of alternate data in enhancing risk management and customer experience
- Build predictive models and machine-learning algorithms for sourcing & collection related projects
- Present information using data visualization techniques
- Propose solutions and strategies to business challenges
- Actively interface with technology to implement and improve business solutions
- Drive external partner engagements (such credit bureaus/ fintech platforms
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