Senior Analytics Manager

Everyday Dose Inc.

About The Position

We’re evolving our Finance organization beyond traditional reporting to build a true Finance & Analytics function — one that powers smarter, faster, data-driven decisions across the business. We’re looking for a Senior Analytics Manager to centralize performance data, strengthen our analytical foundation, and translate complexity into clarity. You will not just build dashboards. You will build clarity. This role owns performance truth across the company — defining KPI standards, building scalable data infrastructure, conducting deep performance analysis, and enabling leadership to make faster, more confident decisions. This is a high-ownership individual contributor role with visibility across Growth, Retail, Marketplace, Operations, and Finance — and the opportunity to build and scale a team over time as the function matures.

Requirements

6–10+ years of experience in analytics, business intelligence, or performance analytics
Experience in CPG, Food & Beverage, subscription businesses, DTC, retail, or multi-channel consumer brands
Strong understanding of business economics, unit economics, and contribution margin drivers
Strong SQL skills and experience working with large, complex datasets
Experience building dashboards in Looker or similar BI tools
Advanced Excel / Google Sheets proficiency
Experience building or improving data warehouse or data lake environments
Ability to synthesize raw data into clear business implications and executive-ready insights
Comfort operating as a hands-on individual contributor in a fast-paced environment
Strong communication skills and an ownership mindset

Nice To Haves

Experience with subscription analytics platforms (e.g., Skio)
Familiarity with accounting and ERP systems (e.g., QuickBooks Online, NetSuite)
Experience with attribution and marketing analytics platforms (e.g., Northbeam, Converge)
Experience with marketplace analytics (Amazon, TikTok Shop)
Experience working with syndicated retail data (e.g., Nielsen, SPINS, IRI)
Exposure to AI-driven analytics, forecasting tools, or automation platforms

Responsibilities

Own Data & Analytics Infrastructure
Centralize and structure data across DTC, retail, marketplace, paid media, subscription, operations, and finance systems
Partner cross-functionally to consolidate fragmented reporting into a scalable data warehouse and/or data lake environment
Build robust data models supporting contribution margin, cohort analysis, and channel-level performance visibility
Establish and document standardized KPI definitions across departments
Reduce reliance on manual spreadsheets and ad hoc reporting
Build Decision-Driving Dashboards & KPI Frameworks
Design and maintain executive-level dashboards in BI tools, especially Looker
Own the company-wide KPI framework, including: Blended and channel CAC
Contribution margin by channel, product, and customer
Cohort-based LTV and payback
Marketplace and retail profitability
Inventory productivity and working capital visibility
Produce clear weekly and monthly executive summaries
Monitor leading vs. lagging indicators and proactively surface risks and opportunities
Drive Cross-Functional Performance Insights
Partner with Growth to evaluate acquisition efficiency, creative performance, and media mix effectiveness
Support Finance with revenue modeling, margin expansion analysis, and investment evaluation
Partner with Retail and Marketplace teams to assess trade spend effectiveness and promotional ROI
Analyze syndicated retail data to identify share trends, velocity shifts, distribution changes, and competitive insights
Deliver actionable recommendations that inform capital allocation and strategic trade-offs
Forecasting, Modeling & Advanced Analytics
Build and enhance financial and operational models grounded in strong business economics and unit economics principles
Support scenario planning and long-range forecasting
Develop predictive analyses such as LTV modeling, churn analysis, demand forecasting, and margin simulations
Leverage AI tools to improve forecasting accuracy, automate insight generation, and detect anomalies
Continuously elevate the analytical sophistication of the organization