DATA501: Data Intelligence Stack Owner

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    "datePosted": "2024-06-06T20:32:27.228Z",
    "description": "<h2>About JerseySTEM</h2>\n<p><strong>All JerseySTEM roles are pro-bono (unpaid) positions.</strong>JerseySTEM is a mission-driven professional network of pro-bono contributors dedicated to improving access to STEM education and career pathways for underserved middle school girls in New Jersey.</p>\n<p>Members contribute their professional skills and leverage their networks in service of the organization’s gender-equity agenda.Membership is a <strong>minimum six-month commitment of approximately six flexible hours per week </strong>and includes a $100 refundable deposit, returned after six months of active membership. K–12 educators, retirees, veterans, interns, and students are exempt from the deposit.</p>\n<h2>Overview</h2>\n<p><strong>This is a pro-bono volunteer position.</strong></p>\n<p>JerseySTEM is seeking an<strong> AI-Forward Data Intelligence Stack Owner</strong> to lead the evolution of our data-to-intelligence pipeline. The scope of this role is strictly focused on the Intelligence Layer of the tech stack, transforming organizational data into automated insights </p>\n<p>You will architect a stack that leverages <strong>Generative AI, Automated Data Pipelines, and Predictive Modeling</strong> to provide real-time, actionable intelligence. You are the bridge between raw data silos and an AI-enhanced decision-making culture.</p>\n<h2>Responsibilities</h2>\n<ul>\n <li><strong>AI-Centric Architecture:</strong> Design and oversee a data stack (Google BigQuery, Vertex AI, or similar) that prioritizes AI readiness and automated data flow.</li>\n <li><strong>Generative Insights: </strong>Implement AI \"Chat-with-your-Data\" interfaces and LLM-driven summarization for stakeholders to interact with organizational data.</li>\n <li><strong>Predictive Analytics: </strong>Move beyond historical reporting to build models that predict volunteer churn, student engagement trends, and fundraising opportunities.</li>\n <li><strong>Automated Governance: </strong>Utilize AI tools to monitor data quality, flag anomalies, and ensure privacy compliance automatically.</li>\n <li><strong>Orchestration: </strong>Integrate data from platforms (Salesforce, Jira, Google Workspace) using AI-friendly ETL/ELT processes that minimize manual intervention.</li>\n <li><strong>Implementation:</strong> Directly configure and code/test the initial data pipelines, AI integrations, and reporting logic before scaling through the lean team.\"</li>\n <li><strong>Team Leadership: </strong>Recruit and mentor a \"Lean Data Team\" focused on modern techniques like prompt engineering for data, automated visualization, and data engineering.</li>\n</ul>\n<h2>Qualifications</h2>\n<ul>\n <li><strong>Applied AI for Analytics:</strong> Strong understanding of how to use LLMs specifically for data extraction, SQL generation, and automated synthesis</li>\n <li><strong>Modern Data Stack Expertise: </strong>Experience with cloud data warehouses and AI-integrated BI tools (e.g., Looker’s Duet AI, Power BI Copilot).</li>\n <li><strong>Data Engineering Mindset: </strong>Proficiency in SQL and Python, with an emphasis on building clean  data for AI consumption.</li>\n <li><strong>Visionary Thinking: </strong>Ability to replace spreadsheets with automated, intelligent solutions<strong>.</strong></li>\n <li><strong>Ability to translate </strong>AI-driven outputs simply to cross-functional partners.</li>\n <li>Comfortable working in a <strong>remote, distributed, member-driven environment</strong>.</li>\n <li><strong>Minimum commitment </strong>of 6 hours per week.</li>\n</ul>\n<h3><strong>Preferred Qualifications</strong></h3>\n<ul>\n <li>Experience building data products, automated reporting agents.</li>\n <li>Previous experience in a leadership role within a tech-focused nonprofit or startup leading through shifts from legacy to automated data ecosystems.</li>\n <li>Familiarity with \"AI-as-a-Service\" platforms and low-code AI automation.</li>\n <li>Retired professionals or those seeking meaningful pro bono work are welcome.</li>\n</ul>\n<h3><strong>Key Outcomes</strong></h3>\n<ul>\n <li><strong>The Intelligent Stack: </strong>A data environment where AI performs the first-layer of analysis.</li>\n <li><strong>Self-Service Intelligence: </strong>Stakeholders can get answers to complex questions through automated agents rather than waiting for manual reports.</li>\n <li><strong>Zero-Latency Insights: </strong>Implementing systems where key stakeholders receive automated proactive alerts and summaries via Chat/Email driven by data anomalies or trends</li>\n <li><strong>Scalable Team: </strong>A high-performing member team trained in AI-forward data practices</li>\n</ul>",
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