Senior Manager, Data Science & AI

The Role

We are moving from traditional analytics to a Google Cloud–centric, AI-driven organization built on BigQuery, dbt, Vertex AI, and Glean.

The ideal candidate thrives in an innovative, fast-paced environment and is collaborative, accountable, ready, and empathetic. We're looking for individuals who believe they can accomplish more as a team and create lasting growth for themselves and others. We hire based on attitude, competency, and commitment. Solarians are ready to advance our world-class solutions in a fast-paced environment and accept the challenge to lead with purpose. If you're looking to build your career with an exceptional team, you've come to the right place. Join SolarWinds and grow with us!

Core Responsibilities

• Define and execute a Data Science & AI roadmap that integrates LLMs, GenAI, and classical ML into core functions (GTM, Product, Finance, Operations).
• Prioritize use cases by expected impact, feasibility, and time-to-value, partnering with Enterprise Data, IT, and business leaders.
• Translate rapidly changing data + AI space (Vertex, Gemini, Glean, agents) into a clear plan for SolarWinds.
• Lead the design of agentic workflows and AI copilots that monitor business KPIs and health signals, perform automated root-cause exploration over governed data, and push proactive, explainable “answers” and recommendations to executives and operators.
• Use LLM orchestration, RAG over BigQuery/dbt models, and Vertex/Gemini to build agents that are grounded, auditable, and safe.
• Own the end-to-end lifecycle for predictive models (e.g., churn, propensity, adoption, expansion, forecasting): problem framing, feature design, model selection, evaluation, deployment on Vertex AI / BigQuery ML with robust MLOps, writebacks into BigQuery, and integration into Tableau, workflows, or agents.
• Ensure AI outputs are anchored in governed dbt models and BigQuery marts to minimize hallucination and maintain executive trust.
• Recruit, mentor, and scale a world-class DS/AI team; set clear expectations for technical quality and business impact.
• Foster a culture of "high-velocity shipping": lightweight experimentation with fast feedback loops, code reviews, reproducibility, and MLOps best practices as the norm, clear measurement of impact and iteration based on results.
• Collaborate tightly with: Data Engineering & Platform (BigQuery, ingestion, performance/cost), Analytics Engineering & BI (semantic layer, dashboards, NLQ), Data Governance & Security (policies, access, responsible AI).
• Act as the internal "how to solve X with AI" consultant: translate ambiguous business problems into tractable DS/AI solutions, explain technical trade-offs, risks, and constraints in clear language, regularly brief GTM, Finance, Product, and Exec stakeholders on what's possible now, what's next, and what's not worth doing.
• Stay at the forefront of AI and LLM research and GCP platform capabilities (Vertex, Gemini, BigQuery ML, Glean), quickly separating hype from practical value; pilot and harden innovations that can become repeatable, governed patterns for the wider organization.

Required Experience

• Experience: 8+ years in Data Science / Machine Learning, with 3+ years in a formal leadership role managing high-impact technical teams.
• Proven track record of taking models and AI solutions into production and delivering measurable business outcomes (revenue, retention, efficiency, or cost).
• AI & Modeling Expertise: Hands-on experience with LLM orchestration and RAG architectures, fine-tuning or adapting foundation models for business-specific contexts, a broad range of statistical and ML methods across classification, regression, time-series, and uplift/propensity modeling, ability to apply these methods to large, messy real-world datasets and ship something that works now, not just in theory.
• Deep Google Stack Experience: Significant, recent experience with Google Cloud Platform, including BigQuery for large-scale analytics, feature stores, and model inputs/outputs, Vertex AI and/or BigQuery ML for model training, deployment, and monitoring, comfort designing solutions that combine BigQuery + dbt + Vertex/BigQuery ML end-to-end.
• Technical Skills: Strong proficiency in Python (and/or R) and SQL; familiarity with common ML frameworks, practical knowledge of MLOps patterns: model versioning, CI/CD, monitoring, retraining policies, integration of predictions and agents into production workflows and tools.
• Mindset & Leadership: Strong bias for action, ability to attract, grow, and retain high-caliber DS/AI talent, thrive in a fast-paced environment with evolving priorities, drive a data- and AI-informed culture across multiple functions.
• Education: Master’s or PhD in a quantitative field (CS, Statistics, Mathematics, Physics, Engineering) preferred, or equivalent deep industry experience.