Senior Data Analyst (m/f/d)

EIT RawMaterials

About The Position

EIT RawMaterials is seeking an experienced Senior Data Analyst to transform complex market and business data into actionable insights that support strategic decision-making, with a particular focus on commodities, minerals, metals, and critical materials markets. The role leads the design and delivery of advanced analytics solutions, develops visualizations, and partners with stakeholders across the organization to provide data-driven recommendations. The analyst will lead reporting and visualization solutions; analyze commodity and macroeconomic data; develop KPIs and strategic insights; support data management, modelling, and analytics enablement; and advise stakeholders across business functions. The role also contributes to analytics governance, data literacy, innovation, and the organization's long-term analytics roadmap. The position is temporary, on a two-year contract with the possibility of extension, and is based in Germany or Belgium.

Requirements

Bachelor's or Master's degree in Computer Science, Data Science, Information Systems, Statistics, Economics, Engineering, Mathematics, or a related quantitative discipline; equivalent professional experience in analytics, business intelligence, or data visualization will also be considered.
At least 5 years of experience in Data Analytics, Business Intelligence, Market Intelligence, Commercial Analytics, or a related analytical role.
Strong experience analyzing commodity markets, pricing data, supply-demand dynamics, market indices, trading data, or risk-related datasets.
Proven track record of delivering business insights, advanced dashboards, and strategic analytical solutions.
Experience working directly with senior stakeholders and supporting executive decision-making.
Advanced expertise in Power BI or equivalent visualization platforms.
Strong SQL skills and ability to work across large and complex datasets.
Proficiency in Python (Pandas, NumPy, Plotly, Matplotlib, Seaborn) and/or R.
Strong understanding of data modelling, including star schemas, semantic models, and KPI frameworks.
Experience with databases, APIs, ETL/ELT processes, and cloud environments such as Azure, AWS, or GCP.
Advanced Excel skills, including Power Query, Pivot Tables, data modelling, and complex formulas.
Strong knowledge of data quality management, validation techniques, and governance principles.
Submit a CV in English.

Nice To Haves

Experience in consulting, professional services, market intelligence, research, commodities, resources, energy, mining, or related industries.
Experience in critical minerals, metals, advanced materials, raw materials, energy, or adjacent sectors.
Experience with time-series analysis, forecasting, and predictive modelling.
Experience with market data providers, commodity intelligence platforms, and financial data feeds.
Geospatial analytics and visualization expertise.
Familiarity with version control tools such as Git.
Knowledge of scenario modelling, risk analytics, and simulation techniques.
Exposure to machine learning applications supporting business and market analysis.

Responsibilities

Lead the design, development, and maintenance of interactive dashboards, reports, and analytical solutions using BI platforms such as Power BI, Tableau, Qlik, or Looker.
Translate commodities market data into visual narratives for executive and operational decision-making; define reporting standards and dashboard design guidelines.
Develop scalable self-service BI solutions, optimize reporting, and drive user adoption through engagement, training, and continuous improvement.
Analyze commodity prices, market indices, supply-demand indicators, trade flows, and macroeconomic datasets to identify trends, risks, opportunities, and correlations.
Develop KPIs, scorecards, and performance metrics; deliver ad hoc analyses for leadership, commercial initiatives, market intelligence, and corporate reporting.
Present findings through reports, presentations, dashboards, and data storytelling, and provide evidence-based recommendations for business growth and strategic planning.
Collaborate with data engineers, data scientists, and subject matter experts on reliable data pipelines, data models, semantic layers, reporting datasets, and analytical frameworks.
Define and implement data quality standards, validation processes, and controls; support integration of internal and external data sources.
Document data definitions, transformation logic, business rules, and analytical methodologies, and identify opportunities to automate reporting.
Advise stakeholders across Strategy, Business Development, Procurement, Innovation, Finance, Market Intelligence, and Leadership; gather requirements and translate them into scalable analytical solutions.
Present analytical concepts to senior leaders and non-technical stakeholders, facilitate workshops and training, mentor junior analysts, and support data literacy and analytics capability development.
Champion visualization, data storytelling, governance, and reporting best practices; ensure compliance with data governance, security, privacy, and regulatory requirements.
Monitor emerging analytics technologies and market trends, evaluate and pilot analytical approaches, and contribute to the analytics roadmap.