Threat Research Analyst

HUMAN•New York, NY

6d•$90,000 - $110,000•Remote

About The Position

The Detection team at HUMAN is dedicated to protecting the internet by disrupting the economics of cybercrime. On Threat Research, we are responsible for identifying bot traffic pretending to be humans viewing ads, understanding how the bad actors are monetizing the invalid traffic, and launching mitigations to stop the bots. We are looking for an Analyst to join our team; someone who is curious, efficient, and possesses a relentless drive for improvement and will use those tools to manage the full-cycle of fraud fighting: from the early stages of exploratory research to the development and launching of statistical detection techniques.

Requirements

Proficiency at writing performant SQL, bonus points for Snowflake, on TB to PB of data
Experience improving processes and implementing tooling to accelerate analysis
Python experience or exposure preferred
AdTech experience or exposure preferred
Good sense of ownership which drives you to find ways to do things better, faster, and leaner; you hold yourself accountable for the quality and accuracy of your work
Love puzzles and trying to think one step ahead of a fraudster; you look to find new and innovative ways to tackle complex problems through meticulous experimentation and application of emerging technologies
Open and transparent and work in tight collaboration with other team members on data projects and cross-departmentally
Communicative and go out of your way to support your team

Nice To Haves

bonus points for Snowflake
Python experience or exposure preferred
AdTech experience or exposure preferred

Responsibilities

Identify novel methodologies to detect invalid and bot traffic
Act with speed to deploy stop-gap mitigations for emerging threats
Deploy robust defenses based on statistical analysis of supply chain data, network & JS signals, and fraud actor behavior
Deliver new customer-facing features through collaboration with the Product and Engineering teams
Build complex queries and notebooks to analyze historical data, including the use of techniques such as: sub-queries, temp tables, complex joins, variables
Participate in week-long rotations with the primary responsibility of Triaging customer and internal inquiries about fraud efficacy by acting as the first line of analysis
Continuously identify opportunities for process and product improvement (e.g. internal tooling, mitigation processes, etc) that reduce the time needed to identify and action a threat
Rigorously document research, analyses, and threat mitigations to build visibility and auditability of work
Experiment! Try new methods of identifying threats. Test out new tooling. If you have ideas, we want you to test them out.