Data Analyst

About Yara International

Yara International operates globally to address critical issues such as resource scarcity, food insecurity, and environmental change through profitable and responsible solutions. Founded in 1905, Yara is committed to feeding the world responsibly and protecting the planet by developing digital farming tools for precision agriculture and collaborating across the food value chain to create sustainable crop nutrition and mineral fertilizer production. The company values diversity, inclusion, safety, and integrity across its workforce of about 17,000 employees in over 60 countries.

Role Overview and Responsibilities

• Design, develop, and implement advanced data analytics solutions using SQL, Python, PowerBI, and Metabase in alignment with industry best practices.
• Independently plan data product features with minimal oversight and quantify the customer journey employing sophisticated analytical methods to enhance conversion rates.
• Examine user behaviors, conversion funnels, and segment customers for insightful business understanding.
• Translate complex business challenges into comprehensive business intelligence outputs including interactive dashboards and automated reporting tools.
• Establish and maintain automated reporting mechanisms that deliver accurate and timely insights.
• Develop analytical frameworks and methodologies autonomously.
• Effectively communicate data-driven results to stakeholders, rendering technical insights accessible and advising on actionable business strategies.
• Forge strong collaborative relationships across various business units.
• Leverage Machine Learning and MLOps technologies, with an emphasis on experience related to large language models, LLM implementation, quality management, and AWS Bedrock or equivalent platforms.
• Coordinate data-centric projects across markets, collaborating with data engineering, development, and product teams to define requirements and ensure data quality standards are met.
• Identify, troubleshoot, and resolve complex data quality issues, escalating major concerns with detailed impact analyses and solution proposals.
• Continuously monitor data quality metrics and contribute to initiatives aimed at improving data quality processes.

Candidate Profile and Qualifications

• A minimum of a Bachelor's degree in quantitative disciplines such as Mathematics, Statistics, Computer Science, or Economics; a Master's degree is advantageous.
• Demonstrable commitment to ongoing learning in analytics and data science through coursework, certifications, or self-study.
• At least three years of experience in data analysis or related analytical roles with progressively greater responsibility.
• Proficient in core data tools including SQL, Microsoft Excel, BI platforms (PowerBI, Metabase), Python for data analysis, data cleaning, and exploratory data analysis.
• Familiarity with secondary skills such as statistical theory, version control systems (Git/GitHub/GitLab), AI/ML applications focused on analytics, cloud data warehousing, API integration, and marketing analytics software (e.g., Google Analytics, WhatsApp).
• Strong soft skills including autonomous task definition and delegation, effective communication with end-users, clear presentation of analytical results to diverse audiences, and accountability for deliverable commitments.

Additional Information

This role is instrumental in converting complex datasets into actionable business insights, pivotal in guiding strategic decisions. The position offers growth opportunities in advanced analytics, business intelligence, stakeholder engagement, and emerging domains such as AI/ML and automation.

Diversity & Inclusion

Yara is dedicated to fostering a diverse and inclusive workplace, affirming equal opportunity for all. The company has integrated Diversity, Equity & Inclusion into its strategic objectives, supported by a global network of more than 400 employee ambassadors.

Recruitment Process

Subject to local regulations, reference and background checks may be conducted as part of the hiring process, with candidates being notified prior to execution.