Data Scientist

Ideal candidate must have:

• Advanced understanding of statistical analysis, ability to apply analytics in all aspects of the business risk and fraud, growth, collections etc
• Credit risk modelling for underwriting and portfolio monitoring using traditional and alternate data sources.
• Preferred experience in banking, payments, B2B/B2C Lending space (unsecured loans or credit card)
• Experience with large data sets and distributed computing (Redshift/Postgres/Spark) a plus
• Experience with building insights using varied/alternate data sources
• Actively collaborate with technology team, product management, operations teams and other stake holders.
• Move seamlessly between business problems and coding.
• Present complicated analytical solutions to a non-technical audience
• Work with very large data sets residing in different data stores in disparate format
• Readiness to work in a highly results-oriented and fast changing landscape in a fintech start-up Qualification:
• BA/BS in Computer Science, Math, Physics, Engineering, Statistics or other technical field.
• Advanced degrees preferred.
• 1+ years of relevant experience in Banking / NBFC domain.
• Technical skills required:
• Fluency with R, Python, and commonly used machine learning frameworks.
• Build key data sets to empower insights, Spark, SQL, MySQL, SAS, and distributed computing.
• Proficient in classical ML algorithms (Linear/Logistic Regression, Decision Trees, Boosting, Clustering etc.); Deep Learning/NLP good to have