About the Role We have built the engine (Snowflake, Sigma, Marketing Automation Platforms), and now we need you to drive the strategic analysis. Abnormal Security is looking for a Lead Marketing Data Analyst who is part detective, part data architect, and part business consultant. In this role, you will own the system, the signal, and the initial theories regarding performance anomalies. You will not just report numbers; you will uncover the "Why" behind our performance. You will partner with our BI Architects and Revenue Marketing leaders to diagnose funnel friction, pioneer our shift from static dashboards to AI-driven "Ask Anything" agentic analytics, and ensure optimal capital allocation. Crucially, you will provide first-pass diagnoses of data trends so our GTM Strategy & Analytics team can make swift, validated business decisions. What you will do Strategic Insights & Root Cause Analysis - Go beyond "what happened" to uncover "why it happened" by proactively identifying trends in campaign performance, pipeline velocity, and conversion rates. - Own the "First Pass" diagnosis: Identify material variances and provide initial possible theories (e.g., ICP mismatch, routing error, or underperformance of expected MQL results). - Quantify the impact of these trends and propose possible corrective actions (The Math + The Logic) to hand off to GTM Strategy for fiscal validation and final decision (The Business + The Budget). - Partner with the Field, Digital, Strategic Events, Integrated Campaigns & Channel Marketing teams to optimize territory-based performance using the new Multi-Touch Attribution (MTA) models. Data Integrity, Funnel Science & Day-to-Day Operations - Maintain reporting hygiene, standard funnel conversion metrics, and recurring dashboards while monitoring performance versus plan. - Act as the "Check Engine Light" for the GTM engine by monitoring data flows between Marketo, Salesforce, 6Sense, and Snowflake to identify silent failures or data quality erosion. - Analyze the "Golden Path" to revenue to determine the optimal mix of touches (digital, event, human) that accelerates a prospect from "Engaged" to "Closed Won". - Validate the output of our AI Agents (e.g., Account Matching, Email Personalization) to ensure automated decisions are accurate. Architecting and Maintaining the "AI Analyst" - Lead the transition from static reporting to dynamic, AI-driven insights by building and training AI agents to automate L1/L2 data questions. - Build and maintain the semantic layer in Sigma/Snowflake that powers our "Ask Anything" capability, ensuring the AI understands our complex B2B business logic (Buying Stages, 6QA, Deal DNA). - Apply your deep understanding of business logic to train the "Ask Anything" AI Agent so it effectively thinks like a strategist. - Design "agents, data structures and functionality" that not only answer questions but suggest the next logical question to the user. Stakeholder Partnership - Serve as the primary data consultant for the Revenue Marketing leadership team. - Translate complex data sets into clear, executive-ready narratives, presenting initial points of view to tee up solutions for strategy validation. - Mentor junior team members and educate the broader marketing org on data literacy and self-serve tools. - Own the end-of-quarter MBO target attainment reporting for the Revenue Marketing team (excluding SDRs). - Partner closely with Strategy & Analytics (who set the targets), Revenue Marketing Leadership, and the FP&A team to validate performance data and ensure accurate, data-backed alignment on bonus payouts. Must Haves - Experience: 7+ years in Marketing Analytics, BizOps, or Data Science within B2B SaaS. - The “Senior Strategic Partner" Factor: Proven ability to influence executive decisions through data. You don't just supply data; you change minds by exercising "Business Judgment," not just "Data Retrieval". - Technical Stack: Expert-level SQL, deep knowledge of Agent Development, Snowflake / Sigma or similar. Deep proficiency with modern cloud data warehouses (Snowflake) and BI tools (Sigma is a strong plus). - Business Acumen: Deep understanding of B2B Marketing and Pipeline funnels (MQL to Closed Won), Attribution models (Multi Touch is a plus), and ABM metrics (6Sense/Demandbase). - Data Science (nice to have): Basic experience and knowledge in building ML based models that can feed context to our agents. - AI Curiosity: Experience or strong interest in configuring AI-driven analytics tools, LLMs for data analysis, or semantic data modeling. - The "Detective" Mindset: You are uncomfortable when the numbers don't make sense and won't stop digging until you find the root cause. Nice to Have - MS degree in Computer Science, Data Science or related field - Experience with algorithms and optimization - Experience working in B2B marketing analytics (especially in cybersecurity) #LI-MC2 At Abnormal AI, certain roles are eligible for a bonus, restricted stock units (RSUs), and benefits. Individual compensation packages are based on factors unique to each candidate, including their skills, experience, qualifications and other job-related reasons. Base salary range: $136,000—$160,000 USD Abnormal AI is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status or other characteristics protected by law. For our EEO policy statement please click here. If you would like more information on your EEO rights under the law, please click here.

• Function as analytics partner for a marketing team, building and scaling marketing reporting capabilities. These include sizing opportunities, establishing consistent tracking, KPIs, and dashboards, plus developing insights into campaign impact on milestones across the customer journey • Automate operating review deliverables to drive source of truth consistency and reduce cycle time • Enable key stakeholders on insights produced and provide data-driven recommendations to improve marketing efficiency, insights and impact • Continue evolving our analytical capabilities through partnership with Data Engineering to influence roadmap and development of datasets

• Drive growth in website traffic and product signups through collaboration with product and research on conversion rate optimization efforts, content distribution, and channel prioritization • Digital campaign management • Collaborate with team members on social media promotion aligned to broader campaigns • Email and lifecycle campaigns • Help communicate the value of Giving Compass products by developing clear messaging • Supporting monthly product launches and feature rollouts • Creating landing pages and product content - including visual elements • Work with product and research to run growth experiments across channels to improve Visitor → signup conversion, Signup → subscriber conversion, Engagement with product features • This includes A/B testing, Landing page optimization, Messaging tests, Campaign iteration • Work with both product and our internal research team to track and improve marketing performance by analyzing important data such as Website traffic, Conversion rates, Engagement metrics, Campaign performance

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description As a Staff Marketing Data Analyst on the Data team, you will serve as the strategic analytics partner to our CMO and Demand Generation team. Your mandate is to increase Marketing-Sourced ARR and Enterprise Pipeline by turning demand generation into a measurable, optimizable revenue engine. This role sits at the intersection of Marketing, Sales, and Data, with a strong focus on enterprise and full-service growth. This is a rare opportunity to operate as a staff-level revenue partner with direct influence on marketing investment, sales conversion, and enterprise growth strategy. What you'll be doing - Drive analysis directly tied to Marketing-Sourced ARR and Enterprise Pipeline, ensuring marketing investments are measurable and defensible. - Leverage AI tools to accelerate revenue analysis, surface funnel insights, and increase experimentation velocity across Marketing and Sales. - Establish and refine attribution frameworks that connect campaigns to pipeline and closed-won revenue. - Analyze behavioral data across website journeys, campaign touchpoints, and qualification flows to identify high-intent enterprise signals. - Diagnose MQL to SQL to closed-won funnel performance and uncover structural pipeline leakage. - Partner with Sales leadership to analyze qualification patterns, call outcomes such as Gong insights, and conversion drivers. - Evaluate paid and organic channel performance based on incremental pipeline and ARR. - Turn organic and inbound traffic into qualified enterprise pipeline through segmentation and funnel optimization. - Shape and prioritize the marketing experimentation roadmap with a clear focus on measurable revenue impact. - Design and analyze statistically sound marketing and funnel experiments, balancing speed and business confidence. - Replace manual reporting with scalable data models and automated analyses using SQL and warehouse tooling. - Establish consistent metric definitions across Marketing and Sales to ensure durable alignment. Qualifications - Proven ownership of revenue-impacting analytics with direct influence on Marketing-Sourced ARR, Enterprise Pipeline, or CAC efficiency in a B2B SaaS environment. - AI-forward analytical practice with clear examples of using LLMs or automation to accelerate insight generation, improve funnel diagnostics, and scale experimentation. - Deep expertise in enterprise B2B funnels including MQL to SQL to closed-won conversion, pipeline leakage identification, and sales acceptance dynamics. - Strong attribution and measurement experience with the ability to design, refine, and defend attribution frameworks in conversations with senior marketing and revenue leaders. - Staff-level strategic influence with demonstrated experience challenging assumptions, reallocating budget based on ROI, and protecting marketing investment discipline. - Strong experimentation judgment with experience designing statistically sound marketing and funnel tests prioritized around revenue impact. - Automation-first systems mindset with advanced SQL proficiency and comfort working across warehouse modeling tools such as dbt, BI platforms, and Python or R. - Experience operating in complex B2B SaaS environments with enterprise sales motions, longer sales cycles, and tight alignment between Marketing and Sales.