Sr. Tech Lead, GTM Applied AI & Analytics
Software Engineering, Data Science
San Francisco, CA, USA
Posted on Feb 26, 2026
Company Description
LinkedIn 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.
Job Description
This role is based in either our Sunnyvale, San Francisco, New York, or Chicago offices.
At LinkedIn, 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 LinkedIn office on select days, as determined by the business needs of the team.
As part of the Product Operations organization, you will leverage one of the richest proprietary datasets in the world to lead high-impact initiatives that deepen intelligence across our members and customers and elevate product quality.
We are seeking a talented and driven technical leader who excels at delivering world-class AI-powered analytic solutions, actionable insights, and measurable business impact. You will design and implement data-driven initiatives that create both immediate value and long-term strategic advantage.
You bring strong technical acumen, product judgment, and business savvy, with applied expertise in modern AI tools and techniques. You combine analytical rigor with a growth mindset to generate scalable, data-driven learnings. You are comfortable navigating large, complex, and ambiguous data ecosystems and influencing cross-functional stakeholders through strong relationship-building and collaboration.
This is a hands-on “player-coach” leadership role. You will architect solutions, write production-grade code using AI tools, and mentor a team of 3–4 data scientists and analytics engineers.
You will own the end-to-end technical lifecycle of complex initiatives — from prototyping AI-driven concepts to deploying scalable, automated systems. Combining the analytical depth of a principal data scientist with executive-level storytelling, your primary goal is to architect and build agentic workflows, predictive models, and automated systems that fundamentally transform how operations teams operate.
Responsibilities
Architect & Build
Basic Qualifications
The pay range for this role is $150,000 to $243,000. Actual compensation is based on multiple factors including skills, experience, certifications, and location. Compensation may vary in other locations due to cost-of-labor considerations.
Total compensation may include annual performance bonus, stock, benefits, and other applicable incentive compensation plans. For additional information, visit: https://careers.linkedin.com/benefits.
Additional Information
Equal Opportunity Statement
We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.
If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation.
Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:
LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
San Francisco Fair Chance Ordinance
Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.
Pay Transparency Policy Statement
As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
Global Data Privacy Notice for Job Candidates
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.
LinkedIn 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.
Job Description
This role is based in either our Sunnyvale, San Francisco, New York, or Chicago offices.
At LinkedIn, 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 LinkedIn office on select days, as determined by the business needs of the team.
As part of the Product Operations organization, you will leverage one of the richest proprietary datasets in the world to lead high-impact initiatives that deepen intelligence across our members and customers and elevate product quality.
We are seeking a talented and driven technical leader who excels at delivering world-class AI-powered analytic solutions, actionable insights, and measurable business impact. You will design and implement data-driven initiatives that create both immediate value and long-term strategic advantage.
You bring strong technical acumen, product judgment, and business savvy, with applied expertise in modern AI tools and techniques. You combine analytical rigor with a growth mindset to generate scalable, data-driven learnings. You are comfortable navigating large, complex, and ambiguous data ecosystems and influencing cross-functional stakeholders through strong relationship-building and collaboration.
This is a hands-on “player-coach” leadership role. You will architect solutions, write production-grade code using AI tools, and mentor a team of 3–4 data scientists and analytics engineers.
You will own the end-to-end technical lifecycle of complex initiatives — from prototyping AI-driven concepts to deploying scalable, automated systems. Combining the analytical depth of a principal data scientist with executive-level storytelling, your primary goal is to architect and build agentic workflows, predictive models, and automated systems that fundamentally transform how operations teams operate.
Responsibilities
Architect & Build
- 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 the Product Operations Applied AI pillar, including key decisions on frameworks, tooling, and practices.
- 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 Data Science and Engineering teams.
- Mentor and develop a team of data analysts and engineers, 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.
Basic Qualifications
- 7+ years of experience in data science, machine learning, or analytics engineering.
- 7+ 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).
- 3+ years of experience with GenAI technologies and frameworks (e.g., LangChain, LLM APIs).
- 3+ years of architecting, building, and deploying machine learning models and/or automated data solutions in production environments.
- BA/BS in Computer Science, Statistics, Operations Research, Engineering, or a related quantitative field (or equivalent practical experience).
- 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.
- Python
- SQL
- Data Science
- Machine Learning
- Model Development & Deployment
The pay range for this role is $150,000 to $243,000. Actual compensation is based on multiple factors including skills, experience, certifications, and location. Compensation may vary in other locations due to cost-of-labor considerations.
Total compensation may include annual performance bonus, stock, benefits, and other applicable incentive compensation plans. For additional information, visit: https://careers.linkedin.com/benefits.
Additional Information
Equal Opportunity Statement
We seek candidates with a wide range of perspectives and backgrounds and we are proud to be an equal opportunity employer. LinkedIn considers qualified applicants without regard to race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other legally protected class.
LinkedIn is committed to offering an inclusive and accessible experience for all job seekers, including individuals with disabilities. Our goal is to foster an inclusive and accessible workplace where everyone has the opportunity to be successful.
If you need a reasonable accommodation to search for a job opening, apply for a position, or participate in the interview process, connect with us at accommodations@linkedin.com and describe the specific accommodation requested for a disability-related limitation.
Reasonable accommodations are modifications or adjustments to the application or hiring process that would enable you to fully participate in that process. Examples of reasonable accommodations include but are not limited to:
- Documents in alternate formats or read aloud to you
- Having interviews in an accessible location
- Being accompanied by a service dog
- Having a sign language interpreter present for the interview
LinkedIn will not discharge or in any other manner discriminate against employees or applicants because they have inquired about, discussed, or disclosed their own pay or the pay of another employee or applicant. However, employees who have access to the compensation information of other employees or applicants as a part of their essential job functions cannot disclose the pay of other employees or applicants to individuals who do not otherwise have access to compensation information, unless the disclosure is (a) in response to a formal complaint or charge, (b) in furtherance of an investigation, proceeding, hearing, or action, including an investigation conducted by LinkedIn, or (c) consistent with LinkedIn's legal duty to furnish information.
San Francisco Fair Chance Ordinance
Pursuant to the San Francisco Fair Chance Ordinance, LinkedIn will consider for employment qualified applicants with arrest and conviction records.
Pay Transparency Policy Statement
As a federal contractor, LinkedIn follows the Pay Transparency and non-discrimination provisions described at this link: https://lnkd.in/paytransparency.
Global Data Privacy Notice for Job Candidates
Please follow this link to access the document that provides transparency around the way in which LinkedIn handles personal data of employees and job applicants: https://legal.linkedin.com/candidate-portal.