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Absorb Software · 2 months ago

Lead Data Scientist – Marketing & Product Analytics

United States

Full-time

Remote

Senior Level, Lead/Staff

7+ years exp

Absorb Software is a remote-first company that provides online training solutions to leading organizations around the world. They are currently seeking a Senior Manager, Data Science to join their Marketing organization, where you’ll drive data-informed decision making across growth, retention, and product strategy.

Corporate TrainingE-LearningSoftwareTraining

Growth Opportunities

No H1B

Responsibilities

Own the Growth & Enablement data-science roadmap tied to company OKRs; quantify impact and prioritize via ROI-based frameworks

Design, run, and interpret rigorous experiments across website/growth and in-product surfaces; choose the right randomization unit (session/user/account), set guardrails, and deliver credible readouts that drive decisions

Improve the cost and quality mix of inbound demand through better targeting, suppression, routing, and budget allocation; partner with Marketing to put models and playbooks into motion

Build interpretable churn/health signals with meaningful lead time; partner with CS to identify and test the highest-impact mitigation levers

Use AI to tap into new qualitative and behavioral sources (e.g., calls, emails, community, support, etc.) to generate relevant insights

Stand up AI enabled tools, automation and workflows to make the marketing and product teams more efficient

Support feature prioritization process with data on customer/ prospect preferences

Provide usage/uptake data & reviews to assess success of feature releases

Partner with PM/Enablement to quantify impact and de-risk bets with experiments or quasi-experimental methods

Collaborate closely with the BI team to deliver impactful reporting

Qualification

Data ScienceStatistical AnalysisSQLPythonMachine LearningModern Data StacksInfluenceClear CommunicationCollaboration

Required

7-10 years in data science across growth / marketing and / or product analytics

Strong statistical toolkit (experimentation design, uplift/causal methods, time-series, retention analysis)

Advanced SQL and Python

Machine learning (ML) proficiency: Capable of developing, evaluating, and productionizing models (e.g., classification, regression, forecasting/uplift) with solid engineering hygiene (versioning, CI/CD, monitoring, docs)

Experience with modern data stacks (Snowflake/BigQuery/Redshift; dbt/Airflow or similar)

Clear communication and influence across executives, PMs, Marketing, CS