Tech Manager- GTM Applied AI & Analytics
LinkedIn · Posted Oct 16
Professional networking, job search, recruiting, online learning, and B2B marketing services
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About the role
The Technology & Product Operations organization drives high-impact initiatives that strengthen LinkedIn's product and GTM operating system, leveraging proprietary data to improve product quality, enable smarter tooling, and reduce friction across member, customer, and GTM experiences. The team builds AI-powered analytic and agentic solutions, predictive models, and automated systems across large-scale data ecosystems. This hands-on player-coach role architects and ships production Python and SQL data products, AI/ML models, and GenAI agentic workflows, while setting technical strategy and mentoring operations and analytics colleagues.
What you will do
- Lead the hands-on design, development, and deployment of scalable data products, AI/ML models (e.g., member friction, customer impact, anomaly detection), and GenAI-powered agentic workflows.
- Define the technical roadmap and architecture for Technology & Product Operations org, including key decisions on frameworks, tooling, and practices.
- Partner with R&D to build applications leveraging our internal platforms, as well as provide input to R&D on enhancements to our technical platforms and data infrastructure
- Write high-quality, production-ready Python and SQL to build and maintain automated data pipelines, advanced analytics, and insight-delivery systems.
- Serve as the subject matter expert on applying modern AI, LLMs, and ML techniques (e.g., RAG, fine-tuning) to solve GTM business problems in partnership with Operations, Data Science and Engineering teams.
- Mentor operations and analytics colleagues on AI tooling and applications, setting a high bar for technical rigor, code quality, and engineering best practices through a lead-by-example approach.
- Translate complex technical concepts and model outputs into clear, concise, and actionable narratives for senior GTM and Operations leadership.
- Collaborate with Product, Engineering, and Data Science teams to operationalize and scale models from prototype to production, ensuring reliability and measurable business impact.
Skills used in this role
What the employer is looking for
- 8+ years of experience in data science, machine learning, or analytics engineering.
- 5+ years of experience in Python for data manipulation (pandas, NumPy), analytics, and ML (e.g., scikit-learn, TensorFlow, PyTorch).
- SQL experience with large-scale data warehouses (e.g., Presto, Trino, Spark SQL).
- 1+ years of experience with GenAI technologies and frameworks (e.g., LangChain, LLM APIs).
- 1+ years of architecting, building, and deploying machine learning models and/or automated data solutions in production environments.
- Bachelors in Computer Science, Statistics, Operations Research, Engineering, or a related quantitative field (or equivalent practical experience).
Preferred qualifications
- MS or PhD in Computer Science, Statistics, or a related quantitative field.
- Experience with modern data stack and automation tools (e.g., Airflow, Databricks).
- Proven ability to lead ambiguous, complex technical initiatives from 0→1.
- Demonstrated experience influencing technical roadmaps in fast-moving environments.
- Resilient, resourceful, and self-directed with a strong bias for action.
- Passion for AI with a clear, strategic perspective on applying machine learning to drive business decisions.
Benefits and support
- Compensation and benefits are detailed in the job posting
About LinkedIn
LinkedIn is the world's largest professional network, connecting over a billion users globally to create economic opportunity. Owned by Microsoft, the platform provides tools for job searching, professional networking, B2B marketing, sales intelligence, and online learning. Through its data graph, it bridges the gap between global talent and enterprise organizations.
- Industry
- Professional Network
- Company size
- 10001+ employees
- Founded
- 2003-05-05
- Location
- Sunnyvale, California, USA
- Funding stage
- Public Company
Funding
Public Company · $103.5M raised
- 2003-11-01Seed$4.7M
- 2004-08-01Series A$10M
- 2007-01-15Series B$53M
- 2008-06-01Series C$22.7M
- 2014-05-15Post Ipo Debt$500M
Leadership
Chief Executive Officer
EVP of LinkedIn and Microsoft Office
President of Platforms and Digital Work
Senior Vice President & Chief Financial Officer
Senior Vice President & Chief Business Officer
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