- Applied data science research to fight spam, scam and fraud attacks in SMS, MMS, e-mail and other mobile telecommunication protocols
- Helping mobile network operators worldwide in localization, identification, monetization and prevention of spam and fraud attacks
- Big Data analysis of Voice/SMS/MMS traffic (>100 million messages per day)
- Data cleaning and preprocessing (data wrangling), exploratory analysis, statistical analysis
- Machine learning, data mining, text mining in different languages
- Data visualization and presentation
- Uncovering activities of organized groups of spammers and fraudsters
- Researching new fraud techniques and designing algorithms for their detection and prevention
- Monitoring and preventing virus and malware distribution vectors in SMS/MMS
- Presenting results to customers, leading discussions about findings and best approaches to manage the fraud attacks .
Key Responsibilities
What will you work with
Statistical tools - R-studio, python
Mavenir s solution for identification of fraud and spam in mobile networks
Unique data sets (Voice/SMS/MMS/RCS communication from all around the world) State of the art fraud detection algorithms Core mobile network systems and technologies Linux OS
Big data tools - Spark, ElasticSearch/OpenSearch, Kafka Data science and machine learning tooling - NumPy, SciPy, MLlib
Job Requirements
- What we expect you already know/have
- Practical experience with statistical analysis or Business Intelligence
- Scripting languages (for example R, bash, python, perl, lua or similar)
- Data visualization and reporting
- Critical thinking and strong problem-solving skills
- Curiosity and willingness to learn new things
- Working proficiency in English
- We appreciate you already know/have - Machine learning and Linux