Qualifications:
- BE/B.Tech/M.Tech/MSc/MCA qualification or equivalent in Computer science/Mathematics/Statistics/IT
Experience:
- Minimum 4+ years of work experience
- Using analytical and statistical means to identify fraud patterns within large data sets using
- Development of Algorithms for Visualization and statistical tools is essential
- Mining and analysing data from databases to drive optimization and improvement of current routines
- Working with stakeholders throughout the organization to identify opportunities for leveraging enrolment and authentication data to drive fraud risk management solutions;
- Developing custom data models and algorithms to apply to data sets
- Using predictive modelling to increase and optimize customer experiences, discover new scenarios where fraudulent activity may happen
- Coordinating with different functional teams to implement models and monitor outcomes;
- Developing processes and tools to monitor and analyse model performance and data accuracy
- Managing the fraud analytics and Investigation team to ensure compliance and meeting the desired targets of fraud detection, investigation and mitigation
- Deep knowledge associated Fraud detection, problem solving, analytical, report writing and communication
- Knowledge of statistical tools and query languages is desirable
- Experience using statistical computer languages, querying databases and using statistical computer languages (R, Python, SLQ, ) to manipulate data and draw insights from large data sets
- Experience working with and creating data architectures
- Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, ) and their real-world advantages/drawbacks
- Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, ) and experience with applications
- Excellent written and verbal communication skills for coordinating across teams
- Experience with distributed data/computing tools: Map/Reduce, Hadoop, Hive, Spark, MySQL,
- Strong hold on R and statistical theories, Algorithms
- Should have experience in using mathematical/statistical models, concepts and theories to analyse and collect data to validate and quantify risk
- Awareness of security concepts is a must
- Good scripting knowledge with unix shell/phython, etc
- Ability to identify opportunities for automation of operational efficiency
- Ability to automate and integrate the tools with REST API/SDK with security dashboard
Learn more about our Managed Detection And Response Services.