Should have analytical bent of mind.
Uses best practices to understand the data and develop fraud statistical, machine learning techniques to build models that address business needs.
Collaborates with the team in order to improve the effectiveness of fraud business decisions through the use of data and machine learning/predictive modelling.
Ability to stretch, learn and deliver with stricter Timelines and non-negotiable SLA TATs.
Analysis of data to identify fraud and provide insights into fraud solution and fraud workflow analysis and contribute towards the success of our fraud analytics initiatives
Transform data into insights, to identify and quantify opportunities to reduce fraud and false positive into a positive business impact.
Use and leveraging internal and external Fraud tools as part of our Fraud operations (e.g., Python, SQL, Spark)
Experience in database such as SQL, Hadoop, NoSQL, and Massively Parallel Processing (MPP) databases.
Proficient and ability to code and develop prototypes in programming languages in Python, Julia, Spark
Build complex analytical concepts/models related to Fraud
Demonstrated analytic agility.
Should have relevant work experience and has worked on Fraud Models in the earlier organisations.
Professional team player and ability to adapt dynamic work environment with a high degree of change
Comfortable with relational and non-relational databases and API development
Salary: INR As per the industry standard
Industry:Banking / Financial Services / Broking
Functional Area:IT Software - DBA, Datawarehousing
Role Category:Programming & Design
Employment Type:Permanent Job, Full Time
Desired Candidate Profile
Academic/Consulting backgrounds and relevant knowledge of Cards & Payment Industry/BFSI
Highly passionate and research oriented mind set is preferable
Added advantage of Winning Kaggle or Analytics Vidya competition
Familiarity with Deep learning techniques like CNN, Auto encoders, Deep belief nets,
Recurrent Neural Network
Familiarity with Tensor Flow
Minimum of 2/4/6 years of fraud analytics experience with focus on statistical/quantitative modelling and/or machine Learning tools (R, Python, Julia etc.) and in using various database tools (e.g. Hadoop, SQL, Spark-MLIB) processing large volumes of structured and unstructured data
Strong understanding of risk and fraud management BFSI domain is desired
Contact Company:National Payments Corporation of India