Digital Marketing Analyst

Come explore opportunities within Brunswick a global marine leader committed to challenging conventions and innovating next‑generation technologies that transform experiences on the water and beyond. Brunswick believes Next Never Rests and we offer a variety of exciting careers and growth opportunities within united teams defining the future of marine recreation.

Innovation is the heart of Brunswick. See how your contributions will help transform vision into reality:

The Digital Analyst is a strategic partner across marketing, product and data teams transforming complex datasets into actionable insights, predictive models and forward‑looking recommendations. This role goes beyond reporting to develop statistical models, forecast frameworks and automated intelligence that directly influence digital product strategy and marketing effectiveness. The ideal candidate is equally comfortable conducting rigorous quantitative analysis and communicating insights clearly to senior stakeholders.

Advanced Data Modeling & Forecasting

• Design and implement statistical models (e.g. regression, time series, clustering, classification) to forecast performance, identify key drivers of marketing ROI and predict user behavior across channels.
• Build and maintain forecasting models to project marketing performance (e.g. CPA, LTV, ROAS) and inform budget allocation decisions.
• Partner with Finance and Performance Marketing teams to optimize media mix using scenario modeling and budget simulations.

Media Analytics and Paid Marketing

• Analyze and optimize paid media channels including Google Ads, Meta Ads and Programmatic.
• Monitor and analyze ROAS, CAC, CPA, CPL, optimal frequency and overall spend efficiency.
• Conduct funnel pathing and user journey analysis using GA4.
• Support attribution analysis, incrementality testing and channel contribution reporting including web properties without eCommerce capabilities.
• Understand different attribution models and incrementality testing.

Strategic Marketing & Product Analytics

• Lead deep‑dive analyses on digital campaign performance across channels (Paid Search, Paid Social, Display, etc.) to identify key levers for growth.
• Develop and refine attribution models to understand marketing effectiveness across touchpoints and inform investment decisions.
• Support Digital Product teams in quantifying feature adoption, conversion funnel performance and retention metrics with statistically sound methodologies.
• Guide A/B and multivariate testing strategies including test design, lift analysis and statistical significance validation.

Data Engineering & Infrastructure Collaboration

• Partner with data engineering teams to define requirements for analytics infrastructure, data pipelines and ETL processes.
• Develop robust data validation, transformation and QA processes to ensure analytical accuracy and consistency.
• Leverage tools such as Azure Synapse to manage large‑scale datasets efficiently.

Dashboarding & Visualization

• Build scalable interactive dashboards and data stories in Power BI to surface insights for stakeholders.
• Deliver reporting frameworks that enable real‑time monitoring of KPIs (e.g. CPC, CTR, conversion rate).
• Perform market research, competitive benchmarking and digital trend analyses to uncover new growth opportunities and strategic threats.

Cross‑Functional Partnership

• Serve as the analytics lead for Marketing and Product stakeholders, helping them define success metrics and measure impact.
• Communicate complex analytical findings in a clear, concise and actionable way to both technical and non‑technical stakeholders, including executives.

• 3 years of hands‑on experience in digital analytics, marketing science or data science roles with demonstrated impact.
• Strong knowledge of Web Analytics tools (GA4, Adobe Analytics, a plus).
• Ability to work with paid media platforms including DV360, Google Ads and Meta Ads.
• Proficiency in SQL and Python (Pandas, Num Py, Scikit‑learn); R or other statistical languages a plus.
• Strong background in statistical modeling, forecasting and experimental design (e.g. A/B testing, causal inference).
• Expertise in working…