Data Scientist

• Perform necessary analysis, such as data quality assessment, recommendation of Generic Score which predicts customer s portfolio, Market share analysis, competitor analysis etc.
• Work extensively on various types of data like Credit, telecom and utility, demographic and other alternative data
• Conduct complex statistical analysis under the supervision of Manager
• Complex data assessment and integration from multiple platforms as required for analytical purposes

Desired traits

• 3+ years professional level quantitative analytical experience, including conducting hands-on analytics projects using generalized regression models, Bayesian methods, clustering, and similar methodologies
• At least 1 year of professional level quantitative analytical experience in Credit Risk, machine learning using random forest, gradient boosting, neural networks, support vector machine, and similar methodologies
• Proficiency skill in hands-on data mining and modeling projects with Python and SQL.
• Strong consultative acumen and ability to understand complex analytical solutions
• Ability to communicate complex quantitative analysis in a clear, precise, and actionable manner
• Ability to create new ideas for analytical solutions to address customers business issues
• Apt with MS Office components (Word, Excel, Access, PowerPoint) and Google G Suite Preferred Experience
• Experience in cloud-based data engineering and/or machine learning with Google Cloud Platform, AWS, or Azure
• Experience working with big data distributed computing tools (Hadoop Streaming, MapReduce, Spark)
• Exposure to Visualization tools such as Spotfire a plus
• Extensive knowledge in Credit Risk Models
• Strong knowledge of credit bureau data is plus Technical Skills - Desirable
• Basic knowledge of SAS
• Strong knowledge of Python and SQL
• Candidates with Google Cloud based machine learning, Spotfire and data engineering experience will get additional weightage