Data Analyst 2 - Detection Efficacy

Abnormal AI empowers enterprises of all sizes to combat cybercrime with our advanced cloud products. As the threat landscape continuously evolves, we emphasize vigilance and adaptability in our defense strategies. The Detection Data Science team plays a crucial role in providing insights into current and historical product performance, emerging attack trends, and opportunities to enhance our detection capabilities. This requires accurate and timely data sourced from numerous product applications and thousands of detection signals across billions of emails. The team integrates all relevant data into a comprehensive analytics pipeline using DBT (Data Build Tool). This pipeline facilitates a wide range of functions, including the creation of metrics and dashboards, data analysis, model development, and the generation of customer reports.

Abnormal AI is looking for a Data Analyst to join the Detection Data Science team. The Data Analyst will focus on extracting actionable insights from product data to inform engineering, product, and go-to-market decisions. This includes deep-dive analysis of detection performance, monitoring of key metrics, designing experiments, and partnering closely with cross-functional teams to surface trends and drive improvements. This role is core to the Data Science team’s mission to enable Abnormal to move quickly, learn continuously, and measure what matters.

• Contribute to the design, development, and maintenance of the DBT analytics pipeline, ensuring accurate representation of system performance and enabling data-driven decision-making across the organization.
• Build scalable, well-structured datasets and develop innovative data models that enhance the accessibility and depth of our analytics capabilities.
• Define and formalize key metrics in collaboration with stakeholders, ensuring they are stable, effective, and aligned with strategic goals.
• Conduct regular audits of metrics across teams and organizational levels to maintain consistency, accuracy, and relevance.
• Analyze complex data to uncover actionable insights that support decision-making, experimentation, and continuous improvement within Detection.
• Partner closely with Detection leadership and team leads to drive adoption and effective use of metrics and analytical outputs.
• Continuously improve processes for metric definition, inspection, and reporting to maximize their impact and usability.
• Provide training and support to teams on interpreting metrics and using analytics tools effectively.

• 3+ years of experience working with large-scale data in analytical or product-oriented environments, with a strong focus on data exploration, interpretation, and communication.
• Proficiency in writing complex SQL queries and building clean, reliable data models to support reporting and analysis.
• Hands-on experience using DBT (Data Build Tool) to transform and organize data for downstream analytics workflows.
• Strong grasp of data analyst best practices, including analysis reproducibility, validating results through testing and sanity checks, and communicating insights clearly to both technical and non-technical audiences.
• Experience with at least one programming language (e.g., Python or R) for data exploration, statistical analysis, and automating reporting workflows; familiarity with DBT and/or Databricks is a plus.
• Bachelor's degree in a quantitative field such as Data Science, Mathematics, Statistics, Computer Science, Information Systems, or a related discipline.
• Demonstrated ability to translate ambiguous business questions into structured analyses and data models optimized for insight generation.
• Strong track record of collaboration with cross-functional partners to deliver high-impact data solutions.

• MS degree in Data Science, Mathematics, Statistics, Computer Science, Information Systems or other related engineering field
• Experience with predictive modeling or statistical analysis techniques to support deeper insights and forecasting.
• Proficiency with business intelligence tools (e.g., Looker, Tableau, Power BI) to build intuitive dashboards and communicate insights effectively.
• Exposure to cloud-based data platforms (e.g., Snowflake, Databricks) and modern data stack tools.

• Analytically Curious: You ask thoughtful questions, challenge assumptions, and dig deep into data to uncover hidden patterns and insights.
• Detail-Oriented Builder: You care about clean datasets, reproducible analysis, and reliable metrics that scale across teams and use cases.
• Insight-Driven Communicator: You can translate complex analytical findings into clear, actionable recommendations for both technical and non-technical audiences.
• Collaborative Partner: You enjoy working cross-functionally with product managers, engineers, and other stakeholders to drive impact through data.
• System Thinker: You understand how product signals connect across platforms and how metrics, models, and tooling must evolve to reflect real-world changes.
• Pragmatic Innovator: You balance the need for speed with the discipline of sound data practices—delivering the right level of rigor to match the problem.
• Growth mindset and ambition: Committed to excellence and willing to seek out personal/professional growth to expand the scope of responsibilities

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