Data Insights - Tech Manager - IC4

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.

This role is based in either our Sunnyvale, San Francisco, New York, or Chicago offices.   

At LinkedIn, we trust each other to do our best work where it works best for us and our teams. This role offers a hybrid work option, meaning you can both work from home and commute to a LinkedIn office, depending on what’s best for you and when it is important for your team to be together.

The Tech & Analytics team builds the analytical and automation foundation that powers LinkedIn's most important Go-to-Market decisions. We partner across Sales, Customer Success, Marketing, and Engineering to create a unified understanding of GTM performance. Our mission is to transform data into proactive insights and intelligent systems that guide LinkedIn's growth and efficiency.

As a Data Insights Tech Lead, you are the technical authority and chief architect for the next generation of our GTM data solutions. This is a hands-on role for a senior IC who will spend a significant portion of their time architecting solutions, writing production-grade code, and mentoring junior data scientists and analytics engineers.

You will be responsible for the end-to-end technical lifecycle of our most complex projects, from prototyping new AI-driven concepts to deploying scalable, automated systems. You will combine the analytical depth of a principal data scientist with the strategic storytelling needed to influence GTM leadership. Your primary goal is to architect and build the agentic workflows, predictive models, and automated systems that will fundamentally change how our GTM teams operate.

Responsibilities:

• Design and deliver enterprise-grade data and analytics products, driving critical business decisions and championing visualization best practices.

• Collaborate closely with data modeling teams to optimize performance and ensure scalable solutions.

• Define and execute a strategic product vision, balancing business needs with technical constraints, and managing all stages of the product lifecycle.

• Develop scalable data products and AI/ML models, integrating modern AI techniques to solve business problems.

• Mentor a team of data scientists and engineers, setting high standards for technical rigor and code quality.

• Translate complex technical concepts into actionable narratives for senior leadership and foster cross-functional collaboration.

• Lead high-impact global data initiatives, architecting business-critical datasets and driving organizational success through data solutions.

• Champion the adoption of data products across the organization, enabling teams to self-serve insights and make informed decisions.

Basic Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Engineering, Mathematics, Statistics, Physics, Economics, Business Information Technology or related field and 4+ years of experience working with data systems or tools in a business setting OR equivalent experience.

Preferred Qualifications

• MS or PhD in Computer Science, Statistics, or a related quantitative field.

• Experience with GenAI technologies and frameworks (e.g., LangChain, LlamaIndex, LLM APIs).

• Experience with MLOps principles and tools (e.g., MLflow, Kubeflow, SageMaker, Vertex AI) for model versioning, deployment, and monitoring.

• Experience with modern data stack and automation tools (e.g., Airflow, Databricks, dbt).

• Deep understanding of GTM financial and operational metrics (e.g., pipeline, ACV, margin, LTV, CAC, Customer Health).

• A self-directed, intellectually curious mindset with a proven ability to lead ambiguous, complex technical projects from 0 to 1.

• A passion for AI coupled with a strong, opinionated perspective on how to strategically apply machine learning to drive business decisions in a fast-moving environment.

• A resilient and resourceful "get-it-done" attitude, with the ability to thrive in a dynamic, fast-paced setting.

• Proven ability to influence a technical roadmap and lead projects in a fast-moving, ambiguous environment.

Suggested Skills

• Data Analysis

• Business Intelligence (BI)

• Data visualization

• Data Storytelling

• Data Architecture

LinkedIn is committed to fair and equitable compensation practices. The pay range for this role is $138,000 - $225,000.

Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to skill set, depth of experience, certifications, and specific work location. This may be different in other locations due to differences in the cost of labor.

The total compensation package for this position may also include annual performance bonus, stock, benefits and/or other applicable incentive compensation plans. For more information, visit .

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 and describe the specific Accommodation requested for a disability-related limitation.

Fill out an Accommodation request here:

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

A request for an accommodation will be responded to within three business days. However, non-disability related requests, such as following up on an application, will not receive a response.

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:

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: