Senior Data Scientist - Customer Analytics and Insights

<h1><strong>Senior Data Scientist • Customer Analytics and Insights</strong></h1> <p><strong><br>Internal Role Title:</strong> Intelligence Engineer • Customer Insights<br><strong>Squad Assignment:</strong> Assigned to the Brain Squad focusing on Customer Insights and Intelligence &nbsp;<br><strong>Reports To:</strong> First Principles Engineer</p> <p>&nbsp;</p> <p><strong>Role Purpose &amp; The Value Mandate: </strong>The <strong>Intelligence Engineer </strong>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.</p> <p>&nbsp;</p> <p><strong>Core Accountabilities &amp; Key Performance Indicator (KPI): </strong>This role is measured by its success in quantifying the business value derived from its insights.</p> <table> <tbody> <tr> <td> <p><strong>Primary Accountability</strong></p> </td> <td> <p><strong>KPI Measurement</strong></p> </td> <td> <p><strong>Success Definition</strong></p> </td> </tr> <tr> <td> <p><strong>Value of Insights Generated</strong></p> </td> <td> <p><strong>Value of Insights Generated (VIG)</strong></p> </td> <td> <p>Documented business actions taken based on the IE's analysis, leading to a measurable improvement in the target <strong>Business Outcome KPI</strong> (e.g., Conversion Rate, Customer Lifetime Value, or Churn Reduction).</p> </td> </tr> <tr> <td> <p><strong>Data Integrity &amp; Usability</strong></p> </td> <td> <p><strong>Data Reliability Score (DRS)</strong></p> </td> <td> <p>Consistency, accuracy, and usability of the analytical data layers and models deployed to production systems for end-users.</p> </td> </tr> </tbody> </table> <p><strong><br>Key Responsibilities (The "How")</strong></p> <p style="padding-left: 40px;"><strong>Data Analysis and Discovery</strong></p> <ul> <li><strong>Customer Pattern Identification:</strong> Conduct deep-dive analyses on customer behavior, transaction histories, and product usage data to identify anomalies, segment opportunities, and predict churn/loyalty events.</li> <li><strong>Hypothesis Testing:</strong> 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.</li> <li><strong>Data Acquisition:</strong> Work with the <strong>Memory Squad</strong> to ensure new data streams required for high-value intelligence (e.g., sentiment data, external market data) are correctly ingested and modeled.<br><br></li> </ul> <p style="padding-left: 40px;"><strong>Model Development and Deployment</strong></p> <ul> <li><strong>Predictive Modeling:</strong> Develop, train, and deploy production-grade statistical and machine learning models (e.g., churn prediction, propensity-to-buy, customer segmentation) into the operational environment.</li> <li><strong>Model Maintenance:</strong> Own the monitoring, retraining, and continuous improvement of deployed models to ensure sustained predictive accuracy and relevance (DRS).</li> <li><strong>Code Quality:</strong> Apply the <strong>Intelligence Engineer</strong> standard, ensuring all model code is clean, well-tested, documented, and adheres to the <strong>Code Quality Score (CQS)</strong> standard.</li> </ul> <p>&nbsp;</p> <p><strong>Required Qualifications</strong></p> <ul> <li><strong>Experience:</strong> 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).</li> <li><strong>Technical Proficiency:</strong> 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).</li> <li><strong>Business Acumen:</strong> Demonstrated ability to understand core business KPIs and translate abstract data insights into concrete, measurable business recommendations.</li> <li><strong>Communication:</strong> Proven ability to present complex data and model results clearly and concisely to both technical and non-technical executive audiences.</li> <li><strong>Mindset:</strong> Outcome-driven, rigorous, and obsessed with the quality and reliability of data.</li> </ul> <p>&nbsp;</p> <p></p> <p class="ds-markdown-paragraph"><strong>Engineer the intelligence that drives growth.</strong></p> <p class="ds-markdown-paragraph">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.</p> <p class="ds-markdown-paragraph">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.</p> <p></p>