TECH002: Data Intelligence Stack Owner at JerseySTEM, Inc.
United States
<h2>About JerseySTEM</h2> <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> <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> <h2>Overview</h2> <p><strong>This is a pro-bono volunteer position.</strong></p> <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> <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> <h2>Responsibilities</h2> <ul> <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> <li><strong>Generative Insights: </strong>Implement AI "Chat-with-your-Data" interfaces and LLM-driven summarization for stakeholders to interact with organizational data.</li> <li><strong>Predictive Analytics: </strong>Move beyond historical reporting to build models that predict volunteer churn, student engagement trends, and fundraising opportunities.</li> <li><strong>Automated Governance: </strong>Utilize AI tools to monitor data quality, flag anomalies, and ensure privacy compliance automatically.</li> <li><strong>Orchestration: </strong>Integrate data from platforms (Salesforce, Jira, Google Workspace) using AI-friendly ETL/ELT processes that minimize manual intervention.</li> <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> <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> </ul> <h2>Qualifications</h2> <ul> <li><strong>5+ years of industry experience in Data and/or SaaS operating environments.</strong></li> <li><strong>Applied AI for Analytics:</strong> Strong understanding of how to use LLMs specifically for data extraction, SQL generation, and automated synthesis</li> <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> <li><strong>Data Engineering Mindset: </strong>Proficiency in SQL and Python, with an emphasis on building clean data for AI consumption.</li> <li><strong>Visionary Thinking: </strong>Ability to replace spreadsheets with automated, intelligent solutions<strong>.</strong></li> <li><strong>Ability to translate </strong>AI-driven outputs simply to cross-functional partners.</li> <li>Comfortable working in a <strong>remote, distributed, member-driven environment</strong>.</li> <li><strong>Minimum commitment </strong>of 6 hours per week.</li> </ul> <h3><strong>Preferred Qualifications</strong></h3> <ul> <li>Experience building data products, automated reporting agents.</li> <li>Previous experience in a leadership role within a tech-focused nonprofit or startup leading through shifts from legacy to automated data ecosystems.</li> <li>Familiarity with "AI-as-a-Service" platforms and low-code AI automation.</li> <li>Retired professionals or those seeking meaningful pro bono work are welcome.</li> </ul> <h3><strong>Key Outcomes</strong></h3> <ul> <li><strong>The Intelligent Stack: </strong>A data environment where AI performs the first-layer of analysis.</li> <li><strong>Self-Service Intelligence: </strong>Stakeholders can get answers to complex questions through automated agents rather than waiting for manual reports.</li> <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> <li><strong>Scalable Team: </strong>A high-performing member team trained in AI-forward data practices</li> </ul>
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