Staff Data Analyst

About the role

Lokalise is seeking a seasoned Data Analyst to join our team. You will play a crucial role in shaping our data-driven strategies by extracting insights from complex datasets. This position offers the chance to significantly impact product development and business decisions. Your work will ensure that data reliably informs our strategic direction and operational excellence. You will be responsible for transforming raw information into actionable narratives for leadership. This role requires a deep commitment to accuracy and a passion for solving problems with numbers. You will act as a bridge between technical teams and business stakeholders through your analytical output. Your contributions will directly influence the roadmap and success of our products in the market.

Key facts

What you'll do

• Examine user behavior and product performance to uncover trends and opportunities for growth.
• Construct and maintain dynamic dashboards and detailed reports for diverse stakeholders across the organization.
• Partner with product and engineering teams to define critical key performance indicators and monitor advancement against goals.
• Lead investigations into complex business questions to deliver clear, data-backed conclusions and recommendations.
• Support the evolution of data models and infrastructure to improve scalability and data reliability.
• Interpret intricate datasets to address specific business challenges and support high-stakes decision-making processes.
• Validate data integrity and ensure consistency across multiple sources to maintain trust in analytical results.
• Translate ambiguous business problems into structured analytical queries and hypotheses for testing.
• Document analytical methodologies and findings to create a repository of institutional knowledge for the team.
• Communicate technical insights to non-technical audiences in a concise and visually compelling manner.
• Monitor the effectiveness of existing metrics and propose refinements or new measures as the business evolves.
• Facilitate cross-functional workshops to align on definitions, goals, and the interpretation of data.
• Proactively identify anomalies or outliers in data streams and investigate root causes to prevent negative impacts.

Requirements

• Bring a minimum of 5 years of hands-on experience in a data analysis role within a professional setting.
• Hold a Bachelor's degree in a quantitative field such as Statistics, Mathematics, Computer Science, Economics, or a related discipline.
• Demonstrate advanced proficiency in SQL for complex data extraction, transformation, and manipulation tasks.
• Show expertise in utilizing data visualization tools like Tableau or Looker to create intuitive and informative views.
• Possess a strong understanding of statistical concepts and analytical methodologies to approach problems rigorously.
• Exhibit the ability to manage multiple priorities and deadlines in a fast-paced remote environment.
• Provide evidence of strong written and verbal communication skills essential for collaborating with global teams.
• Have a proven track record of working with large datasets and performing accurate data modeling.
• Be comfortable working independently with a high degree of self-motivation and discipline.
• Have experience working with version control systems, such as Git, for managing analytical code and documentation.
• Show attention to detail and a commitment to delivering error-free analytical work.
• Understand data privacy principles and best practices relevant to handling business intelligence.
• Be able to adapt to new tools and technologies as the data landscape evolves within the company.
• Have a history of mentoring or collaborating with junior analysts to elevate the overall team capability.

Nice to have

• Experience with Python or R for advanced data analysis and custom scripting to extend analytical capabilities.
• Familiarity with A/B testing frameworks and experimental design to evaluate product changes effectively.
• Previous experience in a SaaS company where subscription metrics and recurring revenue models are standard.
• Knowledge of data warehousing solutions and ETL processes to streamline data flow and accessibility.
• Understanding of machine learning concepts and how they intersect with business analytics.
• Experience using version control for data science projects to ensure reproducibility and collaboration.
• Background in financial or billing-related data analysis to understand revenue implications.
• Familiarity with customer lifecycle metrics and retention strategies in digital products.
• Skills in automating reporting processes to reduce manual effort and increase efficiency.
• Experience with stakeholder management and influencing skills to drive data adoption across departments.

Practical notes

• Visa sponsorship is not available for this role.
• No travel required.
• Competitive salary and benefits package.
• To apply, please submit your resume and a cover letter detailing your relevant experience.