Staff Adaptive Data Analytics Specialist

Discord is about giving people the power to create space to find belonging in their lives. We want to make it easier for you to talk regularly with the people you care about. We want you to build genuine relationships with your friends and communities close to home or around the world. Original, reliable, playful, and relatable. These are the values that connect our users and our employees at Discord. 

Adaptive Data Analytics is a dynamic team responsible for protecting users from Scaled Abuse on Discord including spam, account compromise, and payments fraud.

This highly analytical team develops strategies to address existing and emerging scaled threat vectors, and helps shape broader strategy through data driven insights. Adaptive Data merges together strengths of Data Science, Machine Learning, and Anti-Abuse Engineering to keep users safe. Successful candidates will be highly collaborative and versatile in their approaches, able to communicate technical complexity with a range of technical and non-technical stakeholders and understand policy, privacy, and compliance considerations. This role will report directly to the manager of the Adaptive Data team.

What You'll Be Doing

• Understand and drive down existing and emerging scaled abuse threats in various spam and fraud related problem spaces through anti-abuse automation — utilizing heuristic rules and machine learning classifiers to stop bad actors
• Think both quantitatively and qualitatively to create reports and recommendations shaping safety strategy — improving, optimizing, and innovating our scaled anti-abuse methodology
• Propose projects, features, and other investments with well crafted RFC’s, and secure buy-in from leadership for these initiatives
• Consult with product teams on new features being introduced on Discord, and propose plans to help reduce or remove abusive behavior before it happens
• Manage metrics and incoming streams of reports and appeals from users and communities to identify developing patterns of abuse
• Work cross-collaboratively with other teams, including Product, Safety Engineering, ML, CX in response to complex and time-sensitive issues

What you should have

• 5 years of experience working with scripting languages like Python or Javascript, and expert level proficiency with SQL on large datasets
• 5 years of experience combating scaled abuse online, with proactive and innovative approaches to handle adversarial actors, understanding the tradeoffs and risks that come with this space
• Strong problem-solving, troubleshooting, and investigative skills: we believe in getting to the root of the matter instead of just addressing symptoms
• Strong stakeholder management skills––you’re adept at improving processes and know how to leverage the skills of multiple disparate teams
• Ability to work in a fast-paced environment and make important decisions under pressure
• Excellent communication skills––you can efficiently and eloquently present ideas, updates and results to both technical and non-technical key stakeholders at various levels
• Experience conducting experimentation in production — formulating and testing hypotheses to assess the impact of anti-abuse automation including both rules and machine learning models
• Familiarity with standard software engineering practices, such as spec creation, code review, version control, and writing technical documentation
• A passion for protecting users, bringing a highly empathetic, tenacious, scrappy, creative, and positive mindset to combat bad actors

Bonus Points

• Experience creating and operationalizing innovative new metrics to bring visibility and insights into unmeasured problem spaces
• Experience developing Machine Learning models or feature engineering to improve existing models
• A strong background in statistics or causal inference

The US base salary range for this full-time position is $205,000 to $225,500  equity   benefits. Our salary ranges are determined by role and level. Within the range, individual pay is determined by additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include equity, or benefits.

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