Marketing Data Analytics Manager

PPLSI

1d•$120,000 - $170,000•Remote

About The Position

We are seeking an experienced Marketing Analytics hire to lead the measurement, forecasting, and optimization of our marketing investment across all D2C marketing channels. This role owns the analytical infrastructure that informs how we allocate spend, evaluate channel performance, and project growth. You will partner directly with executive leadership, marketing channel owners, finance, and data engineering to translate complex analyses into clear, actionable recommendations that drive business outcomes. This is a highly visible, cross-functional role for a leader who can move fluidly between deep technical work and executive communication in a fast-paced environment.

Requirements

5+ years of experience in marketing analytics, data science, or a related quantitative field.
Strong grasp of digital marketing metrics, attribution models, and experimentation methods.
Demonstrated expertise building and interpreting multi-touch attribution models and media mix models in production environments.
Proven track record forecasting marketing performance across a diverse channel mix (paid search, paid social, organic, CTV, and others).
Deep experience with LTV / CAC modeling, cohort analysis, and unit economics — ideally in a subscription, DTC, or performance-driven business.
Advanced SQL required.
Proficiency in Python or R for statistical modeling strongly preferred.
Experience with data warehouses (Snowflake, BigQuery, Redshift) and BI tools (Looker, Tableau, or equivalent).
Familiarity with attribution and measurement platforms (e.g., Google Analytics 4, Adobe Analytics, Mix Panel, Siege, Northbeam, Rockerbox, or similar).
Ability to distill complex, technical analyses into clear, concise narratives for executive audiences.
Comfort operating in a fast-paced, ambiguous environment where priorities shift and decisions are made quickly.
Strong business acumen — you understand that models exist to inform decisions, not to be perfect.
High degree of intellectual honesty; willing to challenge assumptions and flag when the data does not support a preferred narrative.
Bias for action; able to balance rigor with speed and know when each is warranted.
Excellent written and verbal communication skills.
Adaptable to learning new platforms and channels. As our channel mix evolves, can quickly get up to speed on unfamiliar tools, data structures, and reporting environments without needing a playbook.
Curious and self-directed; you dig into anomalies rather than paper over them.

Responsibilities

Design, build, and continuously improve multi-touch attribution (MTA) models to measure channel and campaign contribution across the full customer journey.
Develop and maintain media mix models (MMM) to quantify incremental impact of each channel, evaluate saturation curves, and inform strategic budget allocation.
Own forecasting for marketing performance across paid search, paid social, organic, CTV, display, affiliate, and emerging channels — including scenario planning and monthly/quarterly re-forecasts.
Build and evolve LTV and CAC models by channel, segment, and cohort; establish payback benchmarks and inform investment decisions with clear unit economics.
Present findings, trade-offs, and recommendations to executive leadership; translate technical outputs into clear narratives that drive decisions.
Partner with channel managers, finance, product, and data engineering to align on measurement standards, data infrastructure, and go-to-market strategy.
Collaborate closely with channel owners and data engineering to define reporting needs, establish data feeds, and ensure we can reliably report performance in a timely manner for new partnerships and channels.
Distinguish channels that bring in durable subscribers through cohort and Retention Analysis.