LTS Insights Manager, Product Insights

LinkedIn•Chicago, IL

3d•$131,000 - $212,000•Hybrid

About The Position

This role will be based in Atlanta, Bellevue, Chicago, Carpinteria, Detroit, New York City, Omaha, Sunnyvale, San Francisco, or Washington, D.C. 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. We are seeking a highly motivated and experienced Insights Manager to join our team. The ideal candidate will be responsible for leading a team of Insights Program Managers and Data Engineers to transform our operations and data strategy for Scaled Insights. This role will lead a high-performing data team that bridges strategic data initiatives with hands-on technical execution. This role ensures alignment between business goals and data capabilities, fostering a culture of innovation, accountability, and continuous learning.

Requirements

Bachelor’s degree in, Data Science, Computer Science or a related field
5+ years in data roles (e.g., data analytics, data engineering, data science)
2+ years in a leadership role

Nice To Haves

Experience aligning data initiatives with business strategy
Strong analytical, data-driven and problem-solving skills
Excellent communication and presentation skills
Proficiency in data analysis tools and software
Master's degree in a related field
Experience in the technology or software industry
Knowledge of advanced statistical methods and data visualization techniques
Data infrastructure design and Architecture
Proficient in SQL, Python, and data platforms (e.g. Hadoop, HDFS)
Familiarity with data modeling, ETL/ELT, and modern data stack tools (e.g., dbt, Airflow, Snowflake).
Understanding of AI and Machine Learning lifecycle and MLOps

Responsibilities

Translate business objectives into a clear data strategy and roadmap.
Prioritize initiatives that drive measurable business impact.
Collaborate cross-functionally with Data Science, Engineering, Insights SMEs and business stakeholders.
Guide the team in building scalable data pipelines, AI infrastructure, and monitoring platforms.
Ensure best practices in data governance, quality, and architecture.
Stay current with emerging technologies and assess their strategic fit.
Mentor and coach Insights Program Managers and Data Engineers.
Foster a culture of curiosity, experimentation, and continuous improvement.
Promote diversity of thought and inclusive collaboration.
Hold team accountable to True North Metrics (TNM) (e.g. Jira and Refresh SLAs).
Establish KPIs and OKRs to track team performance and project outcomes.
Drive agile practices and iterative delivery.
Manage resource allocation and capacity planning.