Data AI Strategy Data Science Analyst

Are you ready to design intelligent solutions that transform Supply Chain decision-making At Accenture we are reinventing organizations through technology data and artificial intelligence-helping clients unlock new sources of value and measurable impact for their businesses and society. We are looking for a Data Scientist to join our global team. This role focuses on developing advanced analytics and AI models that leverage curated Supply Chain data products (e.g. Active Inventory Demand Shipments Purchase Orders) to generate predictive insights and optimization capabilities. You will play a key role in translating complex business problems into data-driven solutions-designing models that improve forecasting accuracy optimize inventory levels enhance service performance and drive operational efficiency. From exploratory data analysis to model deployment and monitoring you will contribute across the full AI lifecycle-problem framing feature engineering model development validation deployment and performance tracking. As part of our team you will work on cutting-edge initiatives that integrate Machine Learning optimization techniques and AI-driven decision support systems-ensuring solutions are scalable explainable and aligned with enterprise data strategies. While the role is deeply analytical and technical you will also collaborate with data engineers architects and business stakeholders to ensure that analytical models translate into measurable business impact. Key Responsibilities - Translate Supply Chain business challenges into data science problems and analytical frameworks. - Develop predictive and prescriptive models (e.g. demand forecasting inventory optimization service level prediction lead-time analysis). - Perform exploratory data analysis and feature engineering using curated data products. - Design train validate and optimize machine learning models. - Apply statistical techniques and experimentation methodologies to validate impact. - Collaborate with Data Engineers to ensure data readiness quality and scalability. - Support model deployment and monitoring in cloud environments. - Ensure explainability robustness and governance of AI solutions. - Quantify business impact through KPI definition and performance measurement. - Communicate insights and model outcomes to both technical and non-technical audiences. How does the ideal candidate look like - 1-3 years in Data AI projects (strategy and/or technical development) ideally with exposure to Supply Chain Operations or related domains. - Hands-on technical expertise in building AI solutions-experience with- Python (mandatory) - Machine Learning libraries (scikit-learn XGBoost TensorFlow PyTorch or similar) - SQL for data exploration - Strong understanding of- Supervised and unsupervised learning - Time series forecasting - Optimization techniques (basic linear programming or heuristics is a plus) - Model evaluation and validation frameworks - Experience working with cloud-based environments (Azure ML Databricks or similar). - Understanding of end-to-end AI lifecycle experimentation deployment monitoring governance. - Ability to align analytical solutions with business KPIs and measurable value. - Analytical mindset with strong problem-solving skills. - Excellent communication skills simplifying complex analytical concepts for diverse audiences. - Adaptability and collaboration in global fast-paced environments. - Proficiency in English (required) additional languages are a plus. The position is based in Barcelona or Madrid and follows a hybrid work model with some days working from home and others in the office where you can create interesting synergies with the rest of your team. It is essential to reside in Spain and have a work permit in Spain. Technical Skills - Programming Python (mandatory) SQL. - Machine Learning Predictive modeling feature engineering model tuning and validation. - Time Series Forecasting ARIMA Prophet ML-based forecasting methods. - Optimization Techniques Basic operations research or heuristic methods (plus). - Data Visualization Communicating insights through dashboards or visualization tools. - Cloud ML Platforms Azure ML Databricks or similar. - Model Governance Monitoring explainability and performance tracking. Strategic Consulting Skills - Problem Framing Translating business challenges into analytical solutions. - Data AI Strategy Alignment Ensuring models integrate within broader data ecosystems. - Data AI Strategy Ability to define and execute strategies aligned with business objectives. - Business Case Development Quantifying impact defining KPIs and aligning with executive priorities. - Critical Thinking Problem Solving Structured approach to complex challenges. - Communication Presentation Simplifying technical complexity for diverse audiences. - Adaptability Thriving in global fast-paced and evolving environments. #LI-EU