Staff Data Analyst
Lokalise
| Company | Lokalise |
| Category | Data & Analytics |
| Location | Remote role Latvia; Remote role Spain; Remote role United Kingdom |
| Remote | Remote |
| Employment | Not stated |
| Level | Not stated |
| Salary | Not stated by the employer |
| Posted | 16 Jul 2026 |
| Last verified | 30 Jul 2026 |
| Source | Employer career page (greenhouse) |
Description
Who are we
At Lokalise, we make it easy and profitable for businesses to expand into new markets. Our AI-powered localization platform helps companies manage both software and marketing content from a single, unified environment — ensuring every team speaks with one voice across every language and channel.
By automating workflows, integrating with over 60 tools, and centralizing translation memory and terminology, Lokalise enables product, engineering, and marketing teams to collaborate without friction and launch globally up to 10× faster and at 80% lower cost.
Trusted by thousands of businesses across more than 100 countries, Lokalise empowers millions of people worldwide to use digital services in their native languages. Backed by a customer-loved support team, our platform fits seamlessly into your design, development, and content workflows, helping you scale with consistency and control. Location
While our company operates exclusively on a remote basis, you must reside and have the legal right to work in one of the following countries: the United Kingdom, Latvia, or Spain.
This is a full-time, remote position. Please note that we do not engage on a B2B or contractor basis.
About
At Lokalise, data is not a support function, but a competitive advantage. As a Staff Data Analyst , you will sit at the intersection of data, strategy, and business impact, working closely with Finance, Sales, Marketing, and Product to shape how the company understands and acts on its most important metrics.
This is a role for someone who goes beyond dashboards. You will challenge business questions at their root, design analytics solutions that scale, and raise the bar for how data is used and trusted across the organisation. You will bring the analytical depth to cut through complexity, the communication skills to bring stakeholders along, and the ambition to leave a lasting mark on how Lokalise makes decisions.
If you are energised by turning messy, ambiguous problems into clear and actionable insights, and by building the infrastructure and culture that makes that possible, this is the role for you.
You Will
Contribute to developing and implementing a comprehensive analytics strategy that aligns with our business objectives.
Design, develop, automate, and maintain ongoing metrics, reports, analyses, and dashboards on the critical drivers of our business.
Maintain data integrity and quality through the use of tools such as dbt.
Partner with Finance, Marketing, Sales, and Product teams to provide customer insights and identify opportunities for growth and customer acquisition, retention and engagement flows.
Champion the use of data in decision-making, ensuring data accessibility and literacy across all departments.
Champion and embed AI tools and agentic workflows across the data practice, accelerating analysis, automating repetitive tasks, and enabling forward-looking insights, while experimenting with emerging approaches and establishing best practices that continuously raise the team's AI maturity.
You Must Have
A Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Economics, or a related field.
5+ years of experience in data analytics in a SaaS B2B environment in at least one (more is a plus) of the following business areas: Finance, GTM and/or Product.
Proficiency in analytics and data tools and technologies like SQL, Python, DBT, and knowledge of statistical analysis, predictive analytics and experimentation (e.g. A/B testing).
Excellent communication skills, with the ability to translate complex data insights into actionable strategies.
Experience with data visualisation tools (e.g. Metabase, Looker or Lightdash).
Experience working with a version control environment (e.g. git).
Experience working with AI-driven analytics development, implementing reliable and
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