Fraud Analyst - Trust & Safety (T&S)
TextNow
IT, Accounting & Finance
Canada
Posted on Nov 27, 2024
TextNow is seeking a Fraud Analyst to join our Trust & Safety (T&S) team to help us combat fraud and spam on our platform while building more value for our community of users.
You’ll be responsible for strengthening and operating a fraud investigation and mitigation process to help identify and block bad actors who attempt to abuse our service.
You’ll also play a key role in:
- Collaborating with our T&S data scientists and engineers in ML development
- Evaluating and integrating 3rd party technologies and vendors
- Designing new fraud detection methods and tools
Additionally, you’ll work directly with our T&S product team and our customer care team to strengthen our overall T&S system and deliver positive experiences to our customers.
What You'll Do
- Monitor platform trends for potential fraud using T&S technologies and tools
- Analyze large sets of data to identify anomalies and emerging risk patterns
- Conduct detailed fraud investigations to detect bad actors and mitigate abuse
- Prepare comprehensive reports on fraud incidents and propose preventative solutions
- Provide regular updates to management on fraud trends and mitigation efforts
- Partner with other teams including customer care, data science, engineering, product
- Automate threat discovery and monitoring, leveraging internal and external data sources
Who You Are
- Strong data analysis skills
- Excellent written/verbal communicator
- Proficiency in SQL, Excel, Elastic Search
- Collaborative with a customer-first mindset
- Ability to work independently and on a team
- Strong foundation in probability and statistics
- Experience with relational/non-relational databases
- Self-starter with holistic approach and attention to detail
- Proficient in Snowflake, Redshift, Splunk, and similar data lakes
Preferred Experience
- Proficiency in scripting languages like Python, etc.
- Prior experience with telecom, i.e.calling and messaging
- Prior experience mitigating common fraud and abuse attack vectors