Data Scientist

• Define Ads ontologies and metrics for campaigns, budgets, bids, creatives, audiences, and placements.
• Build dbt models and curated marts in Snowflake with clear data contracts, tests, and SLOs.
• Ingest and enrich unstructured Ads content and publish retrieval‑ready datasets using our managed search/vector services.
• Design and evaluate retrieval workflows (RAG) with existing services for hybrid search and re‑ranking; set quality/latency targets and iterate via experiments.
• Design agent reasoning and policies on ads, including tool definitions and human‑in‑the‑loop approvals.
• Establish evaluation suites covering precision/recall, calibration, hallucination rate, latency, and cost.
• Run A/B or uplift experiments to quantify impact and guide iteration.
• Translate Ads problems into agent behaviors and own KPIs such as ROAS lift, pacing accuracy, RCA precision/recall, forecast MAPE, and time‑to‑insight.

Ads AI Analytics Lead

• Lead the analytics center of excellence for Gainsight's GTM organization, with an initial focus on Sales and Customer Success
• Set standards for dashboard design, metric definitions, data governance, and insight delivery across the team
• Own the quality and trust of all GTM reporting, ensuring leadership can rely on the numbers without second-guessing them
• Act as a mentor to peer analysts, focused on technical and business acumen, escalation support, knowledge and skills sharing
• Own end-to-end analytics across bookings, pipeline health, forecasting, GRR, NRR, renewals, and customer expansion
• Partner with the GTM Planning team on evolution of planning models that support AOP, quota setting, capacity planning, and scenario analysis
• Deliver executive-ready dashboards and weekly/monthly/quarterly operating cadences for Sales and CS leadership
• Partner with Finance on bookings-to-revenue reconciliation and board-level reporting
• Proactively surface risks and opportunities, moving from answering questions to anticipating them
• Lead the transformation from static BI dashboards to AI-enabled, self-service data exploration for GTM stakeholders
• Partner with the GTM Data Architect to establish the semantic layer — the business-side definitions of ACV, GRR, pipeline, and churn that enable reliable AI querying
• Design and deploy AI-powered analytical workflows including natural language querying, anomaly detection, and proactive insight surfacing
• Enable Sales and CS leaders to query data independently without routing every question through the analytics team
• Stay current on the evolving landscape of AI analytics tooling and bring forward recommendations
• Serve as a trusted analytical thought partner to Sales VPs, CS leadership, and RevOps
• Translate complex data into clear business recommendations, connecting the numbers to the "so what"
• Support strategic planning processes including territory design, AOP, and Rules of Engagement

Senior Revenue Analytics Lead

• Gather, preprocess, and validate datasets from internal and external sources.
• Identify trends, patterns, and anomalies using statistical and visual techniques.
• Build and evaluate predictive models using machine learning algorithms.
• Create dashboards and visual reports to communicate findings to stakeholders.
• Maintain clear records of methodologies, code, and project outcomes.
• Work closely with cross-functional teams to align data solutions with business needs.

Data Science, AI Intern

• Collaborate with leaders across the organization to develop and execute on a data strategy inline with ActBlue's near and long term goals, including supporting organizational growth through acquisitions and partnerships
• Foster a data centric culture by upleveling our ability to make data-informed decisions and build best in class data products that meet rigorous performance and reliability standards
• Enable and advocate for AI/ML driven products and features across the ActBlue Platform through building scalable machine learning infrastructure that serves production environments and identifying new opportunities to deploy data science and analytics capacity in service of our mission
• Oversee our Data Science, Data Analytics, Data Engineering, and Data Platform teams in a fast-paced, mission-driven environment
• Guide the evolution of our data systems, tools, and architecture to meet the organization's needs, including data consolidation, governance frameworks, and unified data models across multiple entities
• Ensure high-quality communication and a stakeholder-centric approach between our data teams and their internal customers, with an emphasis on responsiveness and partnership during high-stakes moments

Director of Data Science – Engineering

• Bridge the gap between complex datasets and strategic action.
• Synthesize information from various external sources to develop visibility and insights into search recall gaps and emerging topic trends.
• Inform Wikimedia’s strategy for ensuring that people continue to find the content they need.
• Integrate fragmented data to create a unified view of how users discover and use content.
• Translate analytics and complex trends into actionable narratives.
• Develop automated systems to detect under-indexed content.
• Establish metrics and frameworks for content utilization within Large Language Models.
• Collaborate with product leaders to set goals and track success.
• Assess efficacy of new initiatives through experiment design and analysis
• Interpret website performance data to inform UX/UI enhancements.

Senior Data Scientist, Ecosystems

• Serve as an embedded data lead:
• Understand the product – strategy, goals, roadmap, users – deeply enough to identify high-impact, strategic opportunities and risks.
• Use data to steer conversations: bring data-driven hypotheses, challenge assumptions, frame trade-offs, prioritize strategically.
• Translate vague product hunches into sharp analytical questions, and design the right approach to answer them.
• Be the source of truth for KPIs and product metrics: help define and monitor them, and identify trends and drivers.
• Drive decisionmaking with data: Prioritize analyses that meaningfully inform product decisions and change outcomes, reframe analysis requests that won’t do that into ones that will, and design and deliver the resulting analyses properly and rapidly.
• Lead experimentation thoughtfully: guide the team on when and when not to experiment, help enable self-serve experimentation, and focus on frequent, small experiments to speed learning.
• Identify where product strategy and ideas could be better, more easily, or more quickly implemented with the help of AI (ML or GenAI), and help enable this integration.
• Show up as a collaborative leader, not simply a service provider, and help focus work on what matters most.
• Work end-to-end to translate clinical, member, and claims data from our data warehouse into actionable recommendations: work with stakeholders to design reports and dashboards that answer real business questions, design the data flows to support these, and build the required data transformation pipelines.

Senior Data Scientist

• Define and evolve the measurement strategy for Zillow’s Elevate on-site advertising platform, including ad placements, pricing models, inventory optimization, and advertiser value.
• Lead incrementality, lift testing, and experimentation frameworks that support advertiser reporting and internal decision-making.
• Build KPI frameworks that connect ad performance to advertiser outcomes, product decisions, and revenue growth.
• Partner with Ad Product, Ad Tech, Sales, Commercial, and Data Engineering teams to ensure measurement solutions support both monetization and advertiser trust.
• Translate ad performance and marketplace data into actionable insights that shape product roadmaps and go-to-market strategy.
• Collaborate with third-party measurement vendors, platform providers, and data partners to strengthen Zillow’s advertising measurement capabilities.
• Drive cross-functional alignment on experimentation design, measurement standards, and scalable analytical best practices across the ads ecosystem.
• Mentor data scientists, improve analytical systems and data reliability, and identify responsible AI-enabled workflows that increase efficiency while maintaining rigor and governance.

Principal Data Scientist

• Support data collection, cleaning, transformation, and exploratory analysis for ongoing projects.
• Assist in developing, testing, and improving machine learning and LLM models.
• Perform deep-dive analysis to evaluate model behavior, output quality, and performance across different approaches.
• Help refine prompts, evaluation criteria, and testing workflows to improve consistency and outcomes.
• Partner with cross-functional teams to translate business questions into analytical solutions.
• Build reports, visualizations, and dashboards to communicate insights to technical and non-technical stakeholders.
• Document methods, experiment results, and recommendations clearly and thoroughly.
• Participate in team meetings, project discussions, and implementation reviews.

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