Data & AI Strategy Data Science Analyst
Accenture España · Madrid, Community of Madrid, Spain
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- On site
- Full-time
- $75,000 / year
- Madrid, Community of Madrid, Spain
Job highlights
- Design AI solutions for Supply Chain decision-making.
- Develop predictive and prescriptive models.
- Work across the full AI lifecycle.
- Collaborate with global teams.
- Drive measurable business impact.
About the role
About the Role
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), and 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.
Location & Work Model
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.
Key skills/competency
- Data Science
- Artificial Intelligence
- Machine Learning
- Python
- SQL
- Supply Chain
- Predictive Modeling
- Forecasting
- Optimization
- Cloud Platforms
Skills & topics
- Data Science Analyst
- Data Science
- AI Strategy
- Machine Learning
- Python
- SQL
- Supply Chain Analytics
- Predictive Modeling
- Time Series Forecasting
- Cloud ML
How to get hired
- Tailor your resume: Highlight 1-3 years of Data & AI project experience, especially in Supply Chain. Emphasize Python, ML libraries, and SQL skills.
- Showcase technical skills: Detail your experience with ML models, time series forecasting, cloud platforms (Azure ML, Databricks), and AI lifecycle management.
- Demonstrate strategic thinking: Provide examples of translating business challenges into data science solutions and quantifying business impact with KPIs.
- Prepare for interviews: Be ready to discuss your problem-solving approach, communication skills, and adaptability in fast-paced environments. Practice explaining complex concepts simply.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the primary responsibilities of a Data Science Analyst at Accenture Spain?
- The Data Science Analyst at Accenture Spain is responsible for designing and developing advanced analytics and AI models to improve Supply Chain decision-making. This includes translating business problems into data-driven solutions, building predictive and prescriptive models, performing exploratory data analysis, feature engineering, model validation, deployment, and monitoring across the full AI lifecycle.
- What technical skills are mandatory for the Data Science Analyst role at Accenture?
- Proficiency in Python is mandatory for this role. Additionally, strong experience with Machine Learning libraries (e.g., scikit-learn, XGBoost, TensorFlow, PyTorch), SQL for data exploration, and understanding of supervised/unsupervised learning, time series forecasting, and model evaluation frameworks are essential.
- What kind of industry experience is preferred for this Data Science Analyst position?
- While not strictly mandatory, experience with Supply Chain & Operations or related domains is highly preferred. The role involves working with Supply Chain data products like Active Inventory, Demand, Shipments, and Purchase Orders, so relevant industry exposure is beneficial.
- Does Accenture offer remote work for this Data Science Analyst position in Spain?
- This Data Science Analyst position in Barcelona or Madrid follows a hybrid work model, combining days in the office and days working from home. It requires you to reside in Spain and have a valid work permit.
- What are the key strategic skills sought in a Data Science Analyst at Accenture?
- Accenture seeks candidates with strong strategic and consulting skills, including problem framing, the ability to align analytical solutions with business KPIs and measurable value, data & AI strategy alignment, business case development, critical thinking, problem-solving, and excellent communication skills to simplify complex technical concepts for diverse audiences.
- What cloud platforms are relevant for the Data Science Analyst role at Accenture?
- Experience with cloud-based environments such as Azure ML, Databricks, or similar platforms is required. This is crucial for supporting model deployment and monitoring within cloud infrastructures.
- How important is collaboration in this Data Science Analyst role at Accenture?