Responsibilities

• Build predictive models to identify churn risk and surface upgrade/expansion opportunity across our customer base to inform proactive outreach and account prioritization.
• Build look-alike models to identify which prospects resemble our best customers, and own cohort reporting to track how customer segments perform over time.
• Build marketing mix models (MMM) and incrementality analyses to measure the true impact of marketing spend across the full funnel - digital and offline, including events, BeviMobile, and social - and inform marketing budget optimization decisions.
• Identify leading indicators - including proprietary composite metrics - for weekly reporting that give early signal on marketing performance in between full MMM reads.
• Partner with the Marketing Analytics Engineer to inform the data structures your modeling work needs, and ensure the underlying data is accurate and well understood.
• Translate data and analytics into clear insights and recommendations.

Requirements

• 2-4 years of professional experience in data science, applied statistics, or analytics, ideally with exposure to customer/revenue analytics or marketing measurement.
• Hands-on experience building predictive/classification models (e.g., churn, propensity, look-alike) using techniques like logistic regression, gradient boosting, or similar.
• Experience with causal inference or marketing measurement methods (e.g., MMM, incrementality testing, difference-in-differences) - comfortable incorporating both digital and offline channels (eg events, experiential) into your models, not just clean digital data.
• Strong SQL and Python/R for querying, modeling, and analysis.
• Experience with data visualization tools (e.g., Looker, PowerBI, Hex).
• A creative problem solver, comfortable designing a measurement approach when the textbook experiment isn't available.
• You use AI tools in your own workflow to move faster (e.g., exploratory analysis, code, documentation), and think about how to make your models and analyses accessible to AI tools as well as people.
• A proactive, go-getter mindset - you notice what needs to get built before you're asked, and drive your own work to completion without needing to be chased.
• Excellent communication skills - able to translate complex findings into clear, actionable recommendations for non-technical stakeholders.

Benefits

• Comprehensive medical, dental and vision insurance plans with BlueCross BlueShield, 95% paid by employer
• 401(k) with company match
• Flexible PTO plus 12 company holidays, and additional paid days for sick leave, etc
• Generous fully paid parental leave for both birth parents and non-birth parents
• Fully employer paid disability and life insurances
• Wellness and fitness reimbursements
• Monthly stipends for cell phone use and commuting costs
• Onsite snacks, weekly catered lunch, and (of course) unlimited Bevi ... plus composting and terra-cycling, too
• Happy hours, team-building events, bagel breakfasts, Values awards - and more.