Solutions Engineer

About the role

The MMM Solutions Engineer is a critical role bridging media and measurement to deliver measurable results. This role engages pre-SOW, supports data onboarding, prepares for the first model readout, leads methodology walkthroughs, coordinates across teams, and optimizes processes.

Responsibilities

• Product Scoping: Assess product-client fit, define model scope, and ensure accurate SOW language.
• Technical Onboarding: Support data onboarding, answer client data questions, and partner with reporting, delivery, and econometrics teams.
• Pre-Readout Enablement: Prepare for the first model readout, coach the team on framing budget recommendations and strategic decisions.
• Client Data Science Engagement: Lead methodology walkthroughs, field technical questions, and propose solutions.
• Cross-Functional Coordination: Serve as the central point of contact, ensuring continuity, preventing over-promising, and holding stakeholders accountable.
• AI-Powered Efficiency & Process Optimization: Identify and implement AI tools and automation to improve workflow scalability.
• Product Feedback: Synthesize engagement patterns and client feedback to inform feature development and improve the offering.

Requirements

• Mathematical Proficiency: Strong background in data analysis, statistics, or a related technical field.
• Project & Stakeholder Management: Ability to manage multiple concurrent engagements, build timelines, sequence dependencies, and hold cross-functional partners accountable.
• Data Literacy: Comfort with messy data, simplifying complex data sets into clear, actionable insights.
• Strategic Communication: Ability to translate the "why" behind the "what" for internal stakeholders and external clients, including C-suite executives and client data science teams.
• Proactive Ownership: "Maker's Mindset" - proposing solutions and driving projects forward with minimal hand-holding.
• Collaboration & Engineering Empathy: Experience partnering with model builders on technical hand-offs and QA.
• Client-Facing Experience: Comfortable with C-level executives and technical decision-makers; experience in a customer-facing or new-business-oriented role is a plus.
• Automation & AI Fluency: Demonstrated comfort using AI tools and automation to improve process efficiency.

Qualifications

• Education: Bachelor's degree in a relevant field.
• Experience: Minimum 3 years of experience in a similar role.

Skills

• Strong technical background.
• Ability to interpret complex model outputs and translate them into actionable insights.
• Communication skills to coach and enable client-facing teams.
• Strong technical project management.
• Comfort with process engineering and automation.

Benefits

Unlimited PTO, healthcare (medical, dental, vision, life & disability), retirement matching, wellness perks (fringe, Forma, unlimited telemedicine and therapy), parental leave (birthing parents 16 weeks with 100% pay, partners 12 weeks), learning and development, and equity.