Senior Data Scientist • Customer Analytics and Insights

Internal Role Title: Intelligence Engineer • Customer Insights
Squad Assignment: Assigned to the Brain Squad focusing on Customer Insights and Intelligence  
Reports To: First Principles Engineer

Role Purpose & The Value Mandate: The Intelligence Engineer is responsible for transforming raw operational data into actionable customer intelligence that directly drives revenue and profit optimization. This role is not just about building models; it is about providing the company with a clear, quantified understanding of customer behavior, intent, and value. This intelligence serves as the fuel for product development, sales strategy, and overall business decision-making.

Core Accountabilities & Key Performance Indicator (KPI): This role is measured by its success in quantifying the business value derived from its insights.

Key Responsibilities (The "How")

Data Analysis and Discovery

• Customer Pattern Identification: Conduct deep-dive analyses on customer behavior, transaction histories, and product usage data to identify anomalies, segment opportunities, and predict churn/loyalty events.
• Hypothesis Testing: Design, execute, and interpret A/B tests or observational studies to validate business hypotheses and quantify the potential impact of new features or marketing campaigns.
• Data Acquisition: Work with the Memory Squad to ensure new data streams required for high-value intelligence (e.g., sentiment data, external market data) are correctly ingested and modeled.
  
  

Model Development and Deployment

• Predictive Modeling: Develop, train, and deploy production-grade statistical and machine learning models (e.g., churn prediction, propensity-to-buy, customer segmentation) into the operational environment.
• Model Maintenance: Own the monitoring, retraining, and continuous improvement of deployed models to ensure sustained predictive accuracy and relevance (DRS).
• Code Quality: Apply the Intelligence Engineer standard, ensuring all model code is clean, well-tested, documented, and adheres to the Code Quality Score (CQS) standard.

Required Qualifications

• Experience: 5+ years of progressive experience in a data science, quantitative analysis, or advanced business intelligence role, preferably focused on customer-facing metrics (LTV, conversion, retention).
• Technical Proficiency: Expert knowledge of statistical modeling, machine learning techniques, and data manipulation tools (SQL, Python/R). Proficiency in deploying models via cloud services (e.g., Vertex AI, SageMaker, or similar platform tools).
• Business Acumen: Demonstrated ability to understand core business KPIs and translate abstract data insights into concrete, measurable business recommendations.
• Communication: Proven ability to present complex data and model results clearly and concisely to both technical and non-technical executive audiences.
• Mindset: Outcome-driven, rigorous, and obsessed with the quality and reliability of data.

Engineer the intelligence that drives growth.

This is a high-impact role for a Senior Data Scientist who is passionate about moving beyond models to deliver actionable, revenue-driving customer insights.

If you're rigorous, outcome-obsessed, and ready to build the intelligence layer for a dynamic business, apply now. Let's build the future of customer understanding together.