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Analytics Manager
Based on 10 assessments · 1 from real users
29%
Moderate risk
Average realistic automation risk across all Analytics Manager profiles in the dataset.
Score spread
Distribution across 10 profiles.
Middle half of Analytics Managers score between 26% and 31%.
0%
50%
100%
Task breakdown by work type
Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.
Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.
Computer input, real-world output — needs someone to act on it, not just software.
No computer required. Furthest from automation — the strongest human advantage.
Typical tasks
3 synthetic profiles for a Analytics Manager, ordered by automation exposure.
Tab between them to see how task mix drives the score difference.
Mentor junior analysts, review their work, and establish analysis standards and best practices
deep expertise
social core
20%
AA
0%
Conduct exploratory analysis and statistical testing to investigate business questions or anomalies
deep expertise
19%
DD
27%
Extract, clean, and prepare data from multiple sources (databases, APIs, logs) for analysis
18%
DD
53%
Present findings and recommendations to leadership, product, and engineering teams in meetings and written reports
deep expertise
social core
16%
DA
7%
Collaborate with product and engineering teams to define metrics, requirements, and success criteria for new features
deep expertise
social core
13%
AA
3%
Build and maintain dashboards and automated reports tracking KPIs for stakeholders
12%
DD
58%
Collaborate with product and engineering teams to define metrics, requirements, and success criteria for new features
deep expertise
social core
36%
AA
8%
Conduct exploratory analysis and statistical testing to investigate business questions or anomalies
deep expertise
27%
DD
34%
Extract, clean, and prepare data from multiple sources (databases, APIs, logs) for analysis
17%
DD
60%
Build and maintain dashboards and automated reports tracking KPIs for stakeholders
7%
DD
53%
Mentor junior analysts, review their work, and establish analysis standards and best practices
deep expertise
social core
5%
AA
8%
Present findings and recommendations to leadership, product, and engineering teams in meetings and written reports
deep expertise
social core
5%
DA
9%
Conduct exploratory analysis and statistical testing to investigate business questions or anomalies
28%
DD
66%
Build and maintain dashboards and automated reports tracking KPIs for stakeholders
21%
DD
53%
Extract, clean, and prepare data from multiple sources (databases, APIs, logs) for analysis
21%
DD
66%
Collaborate with product and engineering teams to define metrics, requirements, and success criteria for new features
deep expertise
social core
12%
AA
0%
Present findings and recommendations to leadership, product, and engineering teams in meetings and written reports
some context needed
social core
10%
DA
2%
Mentor junior analysts, review their work, and establish analysis standards and best practices
deep expertise
social core
5%
AA
2%
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