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Among data scientists, AI is already used for a large share of the tasks. Measured exposure for data scientists: 46% (high).

Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.

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About the job

We are looking for a Data Analyst to work for our client. The ideal candidate aligns with the responsibilities and qualifications outlined below.

This is a strong opportunity for a curious, detail-minded analyst to turn raw data into insight that business leaders use every day, in a hybrid role based in Cleveland, OH.

Responsibilities

Gather, clean, and analyze data from multiple sources to uncover trends, patterns, and opportunities

Write and optimize SQL queries to pull and transform data for reporting and analysis

Build dashboards and reports in tools like Power BI or Tableau that make complex data easy to understand

Partner with business teams to define metrics, answer questions, and shape reporting requirements

Validate data accuracy and flag quality issues before they reach decision-makers

Present findings and recommendations to stakeholders in clear, plain language

Automate recurring reports to reduce manual effort and improve consistency

Document data definitions, sources, and reporting logic

Support ad hoc analysis requests and special projects as they arise

Qualifications

2+ years of experience in data analysis, business intelligence, or a similar role

Strong SQL skills and comfort working with large datasets

Experience with data visualization tools such as Power BI or Tableau

Advanced Excel skills

Strong analytical thinking and attention to detail

Ability to communicate technical findings to non-technical audiences

Comfortable managing multiple requests in a hybrid work environment

What Our Client Offers

Work that reaches decision-makers, so your analysis shapes real business choices

Room to introduce better reporting practices and automation, not just maintain old reports

Exposure to data from across the business, which keeps the work varied

A team that treats data quality as a shared priority