Data & ML Ops Product Leader

Early Warning; Chicago (IL); Hybrid; USD 101,000 - 152,000; Full time

Benefits offered by this job

Healthcare Coverage

401(k) Plan

Paid Time Off

Parental Leave

Maven Family Planning

Job summary

Early Warning is building the next generation of data analytics products on the Data & AI team. You will translate stakeholder needs into technical data, model, and analytics requirements and collaborate across analytics, MLOps, and engineering to deliver internal data platforms and capabilities.

The Technical Product Manager will define roadmaps, set success metrics, ensure data governance, and support model deployment via AWS and on‑prem pipelines while partnering with diverse business users

Qualifications

• Bachelor’s degree in STEM or related field (or equivalent).
• 5+ years in product management, data management, or consulting with data/analytics focus.
• 3+ years working with data teams and stakeholders, with hands‑on data experience.
• Strong business intuition and ability to explain complex data strategies.

Responsibilities

• Define and deliver roadmap and technical requirements for data and analytics capabilities.
• Understand end-user needs, identify gaps, and drive adoption and user experience improvements.
• Gather data processing/storage requirements for model development and reporting.
• Set success metrics to improve business results and ensure data governance integration.

Skills

Product management

Data management

Agile methodologies

SQL

Python

Tableau

Communication

Stakeholder management

Education

Bachelor’s degree in STEM or related field

Master’s degree in STEM or related field

Tools

Jira

Spark

SQL

Python

Tableau

Job description

Early Warning is building the next generation of data analytics products on the Data & AI team. You will translate stakeholder needs into technical data, model, and analytics requirements and collaborate across analytics, MLOps, and engineering to deliver internal data platforms and capabilities.

The Technical Product Manager will define roadmaps, set success metrics, ensure data governance, and support model deployment via AWS and on‑prem pipelines while partnering with diverse business users