Senior Digital Marketing Analyst

Brunswick Boat Group•Chicago, IL

5d•Hybrid

About The Position

The Senior Digital Marketing Analyst is a strategic partner to marketing, product, and data teams, transforming complex datasets into actionable insights, predictive models, and recommendations. The role helps shape digital product strategy and marketing effectiveness through rigorous analysis, appropriate use of AI-enabled tools, and clear communication with senior stakeholders. The analyst develops statistical and forecasting models, evaluates digital marketing and product performance, supports experimentation, and helps guide media investment decisions. The role also collaborates with data engineering on analytics infrastructure and data quality, builds reporting and dashboards, and conducts market and competitive analyses. This is a hybrid position requiring three days per week onsite. The anticipated annual base-pay range is $87,800–$128,750, and the position is eligible for an annual discretionary bonus.

Requirements

At least 5 years of hands-on experience in digital analytics, marketing science, or data science roles, with demonstrated impact.
Experience using AI-enabled tools in analytics workflows and evaluating their outputs for accuracy, bias, privacy, security, and business relevance.
Expertise with web and marketing analytics platforms such as Adobe Analytics, Adobe Customer Journey Analytics (CJA), Adobe Launch, GA4, Google Tag Manager, and CRM systems.
Ability to work with paid media platforms, including DV360, Google Ads, and Meta Ads.
Proficiency in SQL and Python, including Pandas, NumPy, and Scikit-learn.
Experience building predictive models from large datasets, such as media-platform data, customer databases, and product telemetry.
Strong understanding of data visualization best practices and experience with Power BI, Tableau, Looker Studio, or equivalent tools.
Comfort working with cloud data platforms such as Azure Synapse.
Strong business acumen and ability to influence cross-functional stakeholders using data and analytical insights.
Excellent communication skills and ability to distill complex findings into executive-ready narratives.

Nice To Haves

Proficiency in R or another statistical language.
Background in statistical modeling, forecasting, and experimental design, including A/B testing and causal inference.

Responsibilities

Design and implement statistical models to forecast performance, identify marketing ROI drivers, and predict user behavior across channels.
Build and maintain marketing performance forecasts, including CPA, LTV, and ROAS, to inform budget allocation.
Partner with Finance and Marketing on media-mix and budget-allocation decisions through scenario modeling and simulations.
Work with Marketing teams to define requirements for reliable website measurement frameworks.
Analyze digital campaign performance across paid search, paid social, display, and other channels to identify growth levers.
Develop and refine attribution models to understand marketing effectiveness across touchpoints and inform investment decisions.
Support Digital Product teams in measuring feature adoption, conversion-funnel performance, and retention using statistically sound methods.
Guide A/B and multivariate testing, including test design, lift analysis, and statistical-significance validation.
Partner with data engineering teams to define requirements for analytics infrastructure, data pipelines, and ETL processes.
Develop data validation, transformation, and quality-assurance processes to ensure analytical accuracy and consistency.
Support privacy-aware measurement and first-party data strategies by documenting data lineage, consent requirements, metric definitions, and model limitations.
Use tools such as Azure Synapse to manage large-scale datasets.
Build scalable, interactive dashboards and data stories in Power BI.
Develop reporting frameworks to monitor KPIs such as CPC, CTR, and conversion rate.
Conduct market research, competitive benchmarking, and digital trend analyses to identify growth opportunities and strategic threats.
Serve as analytics lead for Marketing and Product stakeholders, helping define success metrics and measure impact.
Communicate analytical findings clearly and actionably to technical and non-technical stakeholders, including executives.