Senior Data Analyst

We at Yara are part of a global network, collaborating to profitably and responsibly solve some of the world's key challenges - resource scarcity, food insecurity and environmental change.

About the Unit

Yara grows knowledge to responsibly feed the world and protect the planet, to fulfill our vision of a collaborative society, a world without hunger and a planet respected. To meet these commitments, we have taken the lead in developing digital farming tools for precision farming and work closely with partners throughout the whole food value chain to develop more climate-friendly crop nutrition solutions. In addition, we are committed to working towards sustainable mineral fertilizer production. We foster an open culture of diversity and inclusion that promotes the safety and integrity of our employees, contractors, business partners, and society at large. Founded in 1905 to solve the emerging famine in Europe, Yara has a worldwide presence of about 17,000 employees and operations in over 60 countries.

Responsibilities

Strategic Problem Definition & Analysis Leadership

Lead the definition and refinement of complex business problems from a technical and strategic data perspective, ensuring alignment with organizational goals and long-term strategic objectives

Conduct comprehensive stakeholder analysis to understand underlying business needs and translate them into sophisticated analytical frameworks

Advanced Technical Implementation & Development

An Individual Contributor producing data analysis, calls, and requirements production (SQL, Python, Metabase, PowerBI, etc.) while maintaining world-class technical standards and driving innovation in analytical methodologies

Architect and implement complex data models, algorithms and analytical frameworks that support enterprise-level decision making

Stakeholder Management & Strategic Alignment

Independently drive the alignment of business requirements with executive stakeholders, defining advanced metrics, and architecting comprehensive business intelligence solutions (e.g., interactive dashboards, predictive reports) to fulfill strategic objectives.

Expertly communicate and make stories out of complex results and strategic insights to diverse stakeholder, including senior leadership, influencing data-driven decision-making across the organization .

Collaborate strategically with data engineering, development, and product teams to define requirements for advanced analytics & insights tooling, ensuring data infrastructure supports future analytical needs.

Clearly communicate business requirements and analytical insights to stakeholders, defining scope, deliverables, and potential impacts.

Proactively define project workstreams and data solutions by directly collaborating with other teams

Establish and maintain strong relationship with C-Level Executives to ensure analytical initiatives support business priorities

Customer Journey & Business Optimization

Quantify and analyze all elements of the end-to-end customer journey with a high degree of precision, identifying significant opportunities for conversion, engagement, and retention, and proposing strategic interventions.

Develop models and predictive analytics to support personalized marketing and product development strategies

Generate impactful business insights and formulate strategic, data-backed recommendations that drive measurable business outcomes.

Technical Excellence & Data Infrastructure Leadership

Perform and track complex data extraction, rigorous data cleaning, and advanced transformations independently, often designing and implementing robust data pipelines

Produce sophisticated dashboards, reports, and analytics independently.

Proactively understand, ensure, and govern data quality across various datasets.

Troubleshot complex data quality issues, identifying root causes and proposing robust, scalable improvement suggestions.

Define problems and propose solutions based on experience and active listening

Team Leadership

Guide junior data analysts, providing technical expertise, best practices, and fostering their professional development.

Establish performance standards and quality metrics for analytical work across the team

Lead technical training initiatives and knowledge sharing sessions to elevate the analytical capabilities of the entire team

Profile

At least a Bachelor’s degree in a quantitative discipline (e.g., Mathematics, Statistics, Computer Science, Economics) or a closely related field. A Master's degree is a bonus.

At least 5+ years of progressive experience as a Data Analyst or in a similar quantitative, analytical role, demonstrating increasing responsibility and complexity of projects.

Advanced coursework or professional development in statistics, machine learning, business intelligence, or related analytical disciplines

Demonstrated expertise in product analytics, including defining, tracking, and interpreting key performance indicators (KPIs) and user behavior metrics to drive product strategy.

Proven track record of leading high-impact analytical projects that have influenced strategic business decisions

Expertise in experimental design and A/B testing methodologies with statistical significance assessment

Proactively identify, thoroughly troubleshoot, and independently provide robust and scalable solutions to complex data quality issues across diverse datasets.

Proven ability to resolve data conflicts and discrepancies that impact multiple business units

Expert in performing advanced Exploratory Data Analysis (EDA), identifying patterns, anomalies, and correlations, and translating these into actionable business insights.

Advanced expertise in statistical modeling, predictive analytics, and machine learning applications for business problems

Hard Skills:

Advanced-to-Expert Level skills in fullstack Data Skills: with at least one skill to a world-class level.

SQL (Structured Query Language): Expert

Microsoft Excel: Expert

BI Tools (e.g., PowerBI, Metabase): Expert

Python or R (for data analysis): High to Expert

Data Cleaning and Preparation: Expert

Exploratory Data Analysis (EDA): Expert

Statistical Concepts: High

Marketing Analytics Tools (Google Analytics, Whatsapp, etc.): High

Version Control (e.g., Git/GitHub/GitLab): High

AI/ML Application (Analytical Focus): Medium to High

Data Warehousing/Cloud Data Platforms: High

API Integration for Data: Medium

Additional Information

Contact details

Apply no later than

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Knowledge grows through differences

As part of our recruitment process, where permitted by local law, we may conduct reference and background checks. These checks will only be performed when deemed necessary for the nature of the job. Candidates will be informed by HR before any background checks are initiated.