Data Analyst

Staff Data Analyst Remote role Latvia; Remote role Spain; Remote role United Kingdom 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 accurate agentic analytics workflows. It’s a Plus If You Have Experience building retention, churn and lifetime-value models and providing value through their applicability to the business. Experience with causal inference techniques like causal impact analysis, difference-in-differences and/or propensity score matching. Experience working with Snowflake and Hex. Experience in data orchestration tools (e.g. Airflow, Prefect, Astronomer). Experience with cloud platforms (e.g. AWS, Azure, GCP) and cloud data services (e.g. AWS Redshift, Azure Synapse Analytics, Google BigQuery). Experience with orchestration agentic AI platforms (e.g Dust, RelevanceAI, n8n).