Everbridge

Junior Data Analyst

19 February 2025
Apply Now
Deadline date:
£29000 / year

Job Description

About the Role: Support data analysis tasks that are both ad-hoc /as-needed to support better data-driven business and product decisionsScope is initially around  AI/ML risk products, then for SLG/Mobile (data gaps) then larger P&LMust work closely with stakeholders across multiple time zones (need person to be flexible)

What you’ll do:

  • Produce key metrics, dashboards, and reports to support  PM asks (AI/ML initiatives, tech partnerships etc.)
  • Present data findings and insights to internal stakeholders, translating complex data into actionable recommendations.
  • Develop and maintain interactive dashboards for real-time analytics and reporting.
  • Collaborate with cross-functional teams in UK, NZ, India and US time zones, ensuring timely updates and support for all teams.
  • Write, optimize, and troubleshoot SQL queries to access, manage, and analyze data within Snowflake or other relational databases.
  • Assist in machine learning projects by preparing data and evaluating models, applying metrics like precision, recall, and accuracy.
  • Build and maintain a comprehensive data dictionary to standardize and improve data usage across the organization.
  • Support data quality initiatives by troubleshooting and validating data integrity in reports and dashboards.

What you’ll bring:

  • Education: Bachelor’s degree in Data Science, Statistics, Computer Science, or a related field, or equivalent work experience.
  • Some Proficiency in SQL for data querying and analysis.
  • Familiarity with relational database concepts and data structures.
  • Strong understanding of statistical fundamentals and measures.
  • Knowledge of data warehousing principles and ETL processes.
  • Experience with data visualization tools, preferably Tableau.
  • Experience with data warehouse tools, preferably Snowflake.

Preferred Qualifications:

  • Basic knowledge of Python for data manipulation and automation 
  • Prior exposure to machine learning workflows or data preparation for modeling.
  • Foundational knowledge of machine learning concepts and metrics, such as precision, recall, and accuracy
  • Ability to communicate effectively with technical and non-technical team members.
  • Flexibility to work across multiple time zones (UK, US, India, NZ).