Senior Manager, Marketing Analytics

Marketing at Optro is scaling fast, and we need a leader who can turn our marketing data into decisions the business actually acts on. As Senior Manager, Marketing Analytics, you will own the measurement layer for the entire marketing org — campaign and channel performance, attribution, funnel health, and pipeline forecasting — and be the person leaders turn to when they want to know what is working and where the next dollar should go. You will partner directly with marketing and cross functional teams with the visibility and the mandate to shape how we invest behind a growth engine that has already carried us past $300M ARR.

This role is remote and based in Canada.

Key Responsibilities

Reports into Marketing Operations and supports the full marketing organization.

• Own marketing performance measurement end to end — campaign, channel, and program reporting from first touch through closed-won revenue.
• Build, maintain, and continuously improve the attribution and funnel models the marketing org uses to allocate budget, and clearly communicate their assumptions and limitations to stakeholders.
• Bring AI into the marketing analytics stack — apply machine learning and LLM-based approaches to lead and account propensity scoring, pipeline forecasting, channel mix optimization, and automated anomaly detection across campaign performance.
• Build AI-assisted insight generation so that routine "what changed and why" questions are answered automatically and surfaced to marketing leaders, rather than sitting in an analyst queue.
• Evaluate, pilot, and scale AI capabilities in our marketing and analytics tooling, and make clear build versus-buy recommendations grounded in measured impact rather than hype.
• Set the standard for responsible use of AI in marketing analytics — validating model outputs, documenting assumptions, monitoring for drift, and partnering with Security and Legal on data handling.
• Partner with Demand Generation and Events teams to set targets, forecast pipeline contribution, and track performance against plan.
• Design and maintain dashboards and self-serve reporting so marketing leaders can answer routine questions.
• Act as the analytics owner of the marketing data stack — Salesforce, marketing automation, and downstream warehouse tables — partnering with Marketing Ops and Data Engineering on data quality and instrumentation.
• Deliver executive-level analysis and readouts for QBRs, board materials, and annual planning — including budget scenarios and ROI cases for new investments.
• Raise the analytical bar across marketing through mentorship, documentation, and clear standards for how analysis is built and presented.

Attributes for a Successful Candidate

• 7+ years of experience in marketing analytics, marketing operations, or a closely related analytics function, including at least 2 years leading analysts, cross-functional projects, or both. B2B SaaS experience strongly preferred.
• Deep, hands-on SQL skills — you can independently pull, join, and validate data without waiting on another team.
• Demonstrated ownership of B2B funnel and attribution measurement. You have built or substantially rebuilt a multi-touch attribution or pipeline model and defended its methodology to skeptical stakeholders.
• Hands-on experience applying machine learning or AI to a business problem — propensity or lead scoring, forecasting, segmentation, or automated insight generation — including a clear point of view on when a model is the right tool and when it is not.
• Exposure to ABM platforms (6sense, Demandbase) or to media mix modeling and incrementality testing at scale.
• Fluency with the modern marketing data stack: Salesforce, a marketing automation platform (Marketo, HubSpot, or similar), and a BI tool (Tableau, Looker, Power BI, or similar).
• Strong executive communication. You can compress a complex analysis into a single clear recommendation a CMO or CRO can act on.
• A genuine partnership mindset. You work shoulder to shoulder with marketing ops, demand gen, sales ops, and finance rather than delivering reports over the wall.

Nice to Have

• Experience with dbt, Python or R, and a cloud data warehouse (Snowflake, BigQuery, Redshift) for modeling marketing data.
• Experience supporting an enterprise, multi-product go-to-market motion.
• Experience building with LLM APIs or AI-assisted analytics tooling (for example, natural-language querying over marketing data, or automated narrative reporting).