Lead - Data Scientist
We have an excellent opportunity with NBFC into Risk Analytics.
Position : Lead - Data Scientist
Position Reports To : Head Analytics
Location : Kurla, Mumbai
Background :
- We are looking for a self-motivated individual who is looking for a challenging career in data science. The individual should be outcome oriented with excellent foundation in statistics theory and the ability to understand dynamics of business.
- He/she will be responsible for designing and developing data-driven solutions to address business problems and independently manage end-to-end project communication with business partners. The ideal candidate displays a proactive learning attitude and enjoys working in an high-energy fast-paced environment.
Brief of the position :
- Establish the advantage of using data science in various facets of SME lending, including (but not restricted to) credit scorecards & portfolio monitoring frameworks, business insights, campaign management, propensity and pricing
- Design, develop and implement machine learning applications
- Evangelize the use of alternate data in enhancing risk management and customer experience
- Actively interface with technology to implement and improve business solutions
- Drive external partner engagements (such credit bureaus/ fintech platforms)
Domain knowledge :
- Analytics project experience related to lending products with a sound understanding of analytics use cases
- Demonstrated track record of having applied data science methods in multiple business situations, on loans businesses
- Knowledge of SME business would be a big plus
Strengths and Soft skills :
- Excellent problem-solving skills
- Excellent written and verbal communication/ presentation skills
- Experience of managing direct reports/ project delivery/ creating sales pitches /presenting to prospective clients
- Managing cross functional stakeholders at senior levels
- Experience of having managed projects with external consultants/ credit bureaus/ rating agencies/ other vendors
Technical skills :
- Statistical methods / machine learning: supervised (e.g. regression, SVM, gradient boosting, random forest, neural networks), unsupervised (e.g. clustering, factor analysis, principal component analysis, k-means), text mining & Web scraping
- Tools - high proficiency in at least one of SAS + Python/R; experienced in at least one BI tool (like SAS VA, Tableau, Power BI); understanding of AWS platform; knowledge of no SQL DB and query language will be a big plus
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