Principal Analyst (Data Scientist)

Factspan Analytics; United States; Remote; USD 120,000 - 170,000; Full time

Job summary

Factspan Analytics seeks a Data Scientist to own end-to-end ML lifecycle—from problem framing through deployment and monitoring. You will build models for CLV, churn, and behavioral segmentation to fuel marketing campaigns, and shape experimental design with rigorous A/B testing and causal inference.

Candidates should have strong Python/SQL skills, cloud experience, and a track record in marketing or consumer analytics, with effective communication to executives.

Qualifications

• Experience with statistical and ML models, for both supervised and unsupervised learning.
• Hands-on expertise in Python and SQL is required.
• Knowledge of working in cloud platforms and familiarity with MLOps.

Responsibilities

• Develop Customer Lifecycle Intelligence: Lead the development of predictive models for Customer Lifetime Value (CLV), churn or buying propensity, and behavioral segmentation to drive marketing campaigns.
• Optimize Experimental Design: Design and implement A/B testing and Causal Inference roadmap, ensuring rigorous statistical validation for incrementality testing and lift studies.

Skills

Python

SQL

MLOps

Cloud Platforms

Communication

Tools

Python (Pandas)

SQL

Cloud Platforms

MLflow

Job description

Role Overview:

We are looking for a Data Scientist with strong end-to-end ownership across the entire machine learning lifecycle - spanning problem framing, data exploration, feature engineering, model development, experimentation, deployment and monitoring.

Key Responsibilities:

• Develop Customer Lifecycle Intelligence: Lead the development of predictive models for Customer Lifetime Value (CLV), churn or buying propensity, and behavioral segmentation to drive marketing campaigns.


• Optimize Experimental Design: Design and implement A/B testing and Causal Inference roadmap, ensuring rigorous statistical validation for incrementality testing and lift studies.

Technical Excellence & Code Standards:

• Conduct rigorous peer reviews of Python/SQL code and ensure the scalability of ML pipelines in production (MLOps).


• Stakeholder Influence: Translate technical model outputs into actionable \"Growth Levers\" for the CMO and Product heads, aligning data science initiatives with marketing targets.


• Communication: Excellent communication, both verbal and written is a must.

Technical skills:

• Experience with statistical and ML models, for both supervised and unsupervised learning. Hands-on expetise in Python and SQL is required. Knowledge of working in cloud platforms and familiarity with MLOps.


• 5+ years of professional experience in Data Science, with at least 2 years focused specifically on Marketing or Consumer Analytics.


• Proven track record of leading or working through the full data product lifecycle (from ideation to production