Senior Manager, Data and AI Products

Company Description

Linked In is the world’s largest professional network, built to create economic opportunity for every member of the global workforce. Our products help people make powerful connections, discover exciting opportunities, build necessary skills, and gain valuable insights every day. We’re also committed to providing transformational opportunities for our own employees by investing in their growth. We aspire to create a culture that’s built on trust, care, inclusion, and fun – where everyone can succeed.

Join us to transform the way the world works.

At Linked In, our approach to flexible work is centered on trust and optimized for culture, connection, clarity, and the evolving needs of our business. The work location of this role is hybrid, meaning it will be performed both from home and from a Linked In office on select days, as determined by the business needs of the team. This role can be based in either our San Francisco, Sunnyvale, Bellevue, Chicago, or New York offices.

The Senior Manager, Data & AI Products will lead a high-performing team of data professionals while remaining hands‑on in the technical delivery of next‑generation GTM data and AI products for Linked In Marketing Solutions.

In this role, you will drive the complete technical lifecycle, from initial prototyping to the deployment of scalable, automated systems. Success requires a unique blend of expertise in data science, analytics, and agentic AI, coupled with a strong product sense and the communication skills needed to influence cross‑functional stakeholders. Your core mission is to architect and build the automated data solutions, agentic workflows, and AI models that will fundamentally transform GTM operations and drive measurable business ROI.

• Drive the design and end‑to‑end deployment of scalable data products, AI/ML models (e.g., customer health, propensity, and forecasting), and GenAI‑powered agentic workflows, remaining hands‑on in technical delivery.
• Define the technical roadmap and architecture for the GTM Data Products pillar, making key decisions on frameworks, tools, and MLOps practices.
• Mentor and develop a team of data scientists, analytics engineers and analysts, setting a high bar for technical rigor, code quality, and engineering best practices.
• Partner with GTM Operations & Sales leadership to identify key business opportunities, and recommend technical solutions to maximize ROI.
• Collaborate with Technology Teams, Product, Engineering, and Data Science partners to operationalize and scale solutions ensuring reliability and business impact.
• Translate highly complex technical concepts and model outputs into clear, concise, and actionable narratives for senior GTM and Operations leadership.
• Act as the subject matter expert in applying modern AI, LLMs, and ML techniques (e.g., RAG, Classification Models, Regression Models, etc.) to solve concrete GTM business problems and drive measurable business ROI in partnership with central Data Science and Engineering teams.
• Design and lead experimentation frameworks (e.g., A/B Testing) to measure the business impact of AI products, models, and workflows.

• 10+ years of experience in data science, data product management, analytics engineering or similar role.
• 3+ years of experience as a people manager.
• Experience in advertising/media and/or go‑to‑market.
• Experience in Python for data manipulation (e.g. Pandas, Num Py), analytics, and ML (e.g., Scikit‑learn, Tensor Flow, PyTorch).
• Experience architecting, building, and deploying machine learning models and/or automated data solutions into a production environment.
• Experience in SQL with large‑scale data warehouses (e.g., Presto, Trino, Spark SQL) and using and developing reports, metrics, and dashboards.
• Experience with modern data stack and automation tools (e.g., Airflow, Databricks, dbt).
• BA/BS/MS degree in a quantitative field (e.g., Computer Science, Statistics, Operations Research, Engineering) OR equivalent practical work experience.

• Experience with sales planning and/or customer segmentation.
• A passion for AI coupled with a strong perspective on how to strategically apply machine learning to drive business value.
• Experience with MLOps principles and tools (e.g., MLflow, Kubeflow, Sage Maker, Vertex AI) for model versioning, deployment, and monitoring.
• Experience with GenAI technologies and frameworks (e.g., Lang Chain, Llama Index, LLM APIs).