- Expérience
- Jusqu'à 2 ans
- Salaire
- 70 000 à 95 000 USD par an
- Ouvertures
- 1
- Publié
- il y a 1 heure
- Mode de travail
- Travaillez à domicile
- CV
- Candidature requise
Description de l'emploi
About the Role
Join a fully remote insurance and risk-advisory consulting firm in the United States committed to accuracy and trust in data. As an AI Data Analyst, you will ensure the reliability and integrity of data that powers AI applications and decides business outcomes. Your efforts will prevent erroneous data from undermining trust and affecting decision-making. This early-career position offers a clear advancement trajectory from monitoring data quality to managing pipelines and models independently.
Responsibilities
- Manage and maintain regular analytics and reports that support the company's operations and AI tools, developing new data views as needed while phasing out unreliable ones.
- Identify and resolve discrepancies in data before issues become apparent to others, providing clear explanations of data errors.
- Standardize definitions across analytics platforms to ensure consistency, such as a unified understanding of "active client."
- Translate ambiguous inquiries from team leads into credible, accurate data insights while clarifying the limitations of available data.
- Collaborate closely with teams from operations, finance, and client engagement to promote adoption and trust in data analytics one individual at a time.
- Gradually learn and expand knowledge of data pipelines and warehouse models over the first year, progressing to actively enhancing them.
Requirements
- 0 to 2 years of professional experience handling data or a strong initial background in consulting, professional services, or customer-facing roles.
- Proficiency in SQL, including writing queries, joining tables, and analytical reasoning with data, which is essential for this role.
- Understanding of data quality issues and the complexities of working with imperfect datasets.
- Demonstrated experience with AI tools like ChatGPT, Claude, or custom-built automations.
- Motivation to acquire skills in dbt, data warehouse modeling, and pipeline architecture.
- Preferred but not required: experience with BI platforms such as Tableau, Power BI, or Looker; familiarity with dbt, Snowflake, BigQuery, or git; basic Python skills; and a background in consulting or professional services.
Why Join Us
The company supports your growth from an analyst role to owning the data infrastructure and analytics engineering responsibilities, with corresponding compensation. The remote-first culture values developing versatile individuals who stay connected to the business's core challenges rather than hiring externally for scarce roles.