Customer Analytics Lead: AI-Driven Insights (Remote)

OpenKrill; United States; Remote; USD 120,000 - 180,000; Full time

Benefits offered by this job

Fully remote within United States

Strategic impact on revenue and growth

Cross-functional exposure

Job summary

OpenKrill is seeking a Customer Analytics Specialist in the United States to transform customer data into actionable insights, improving retention and driving revenue growth. You will build dashboards, predictive models, and AI-powered tools, collaborating with Customer Success, Account Management, and leadership.

Responsibilities include health analytics, renewal/expansion insights, data infrastructure, and automated reporting while ensuring data quality and cross-functional alignment.

Qualifications

• 8+ years in BI/data analytics roles or equivalent.
• Proficient in Power BI or Tableau for dashboards/reports.
• Experience with Python and pandas for data analysis.
• Familiarity with CRM, ERP, WMS data structures.
• Strong business acumen and stakeholder communication.

Responsibilities

• Develop and maintain customer health and retention analytics.
• Create renewal and expansion dashboards with win probabilities.
• Produce quarterly value reports for executives.
• Automate reporting and ensure data quality across systems.
• Collaborate with Ops/IT to improve data pipelines and definitions.
• Lead AI-driven analytics initiatives and validate outputs.
• Drive improvements to reduce manual reporting and speed insights.

Skills

Power BI

Tableau

Python

Pandas

Analytical thinking

Stakeholder comms

Churn modeling

Data storytelling

Tools

Power BI

Tableau

CRM data platforms

Job description

OpenKrill is seeking a Customer Analytics Specialist in the United States to transform customer data into actionable insights, improving retention and driving revenue growth. You will build dashboards, predictive models, and AI-powered tools, collaborating with Customer Success, Account Management, and leadership.

Responsibilities include health analytics, renewal/expansion insights, data infrastructure, and automated reporting while ensuring data quality and cross-functional alignment.