Data Science Associate (Fashion)

Metyis is growing! We are looking for a Data Science Analyst to join our Data and Analytics team in Porto. The ideal candidate should have 3+ year of professional experience in data science.

Requirements

Who we are

We are Metyis, a forward-thinking, global company that develops and delivers solutions around Big Data, Digital Commerce, Marketing and Design and provides Advisory services. We have offices in 15 locations with a talent pool of 1000+ employees and more than 50 nationalities, dedicated to creating long-lasting impact and growth for our business partners and clients.

Together with HUGO BOSS, our esteemed business partner, we have embarked on a joint venture and created the HUGO BOSS Digital Campus, dedicated to increasing the data analytics, eCommerce and technology capabilities of the company and boosting digital sales. The HUGO BOSS Digital Campus employees will help create a state-of-the-art data architecture infrastructure, advanced business analytics, and the development and enhancement of HUGO BOSS’ eCommerce platform and services.

This collaborative environment will provide the capabilities required for HUGO BOSS to maximise data usage and support its growth trajectory towards becoming the leading premium tech-driven fashion platform worldwide.

We are Metyis. Partners for Impact.

What we offer

• Opportunity to accelerate the pace of digitalization through advanced technology, business intelligence, and analytics.
• Driving high-impact insights enhancing decision making across the entire organization.
• Interaction with senior business leaders on regular basis to drive their business towards impactful change.
• Become part of a fast-growing international and diverse team

What you will do

• Conduct advanced data analysis focused on omnichannel customer behavior, CRM performance, and sales effectiveness across digital and physical touchpoints (specific for our team).
• Translate business problems into analytical solutions, from requirement gathering to model deployment and monitoring.
• Build, deploy, and maintain machine learning models (e.g. churn, CLV, segmentation, personalization) using modern MLOps frameworks (e.g. MLflow, GitL).
• Leverage Databricks, Azure, or similar cloud infrastructure for scalable data processing and model deployment.
• Use Python, PySpark, and common ML libraries (e.g. scikit-learn, XGBoost, LightGBM, etc.) for data transformation, model development, and evaluation.
• Apply statistical methods (e.g. hypothesis testing, A/B testing, confidence intervals) to validate performance and derive actionable insights.
• Communicate findings and recommendations clearly through compelling storytelling and visualizations.
• Collaborate with cross-functional stakeholders (e.g. Business teams, Data Engineering, IT teams) and contribute to customer-centric strategies..
• Support team development through knowledge sharing, collaboration, and participation in agile working models.

What you’ll bring

• 3–5 years of experience in data science or advanced analytics, ideally in retail or e-commerce.
• Master’s degree in a quantitative field such as Data Science, Applied Mathematics, Computer Science, or Engineering.
• Proven ability to manage the full lifecycle of an ML solution – from business understanding, data wrangling, and modelling, to production deployment and monitoring.
• Hands-on experience with MLflow, Git, and MLOps frameworks.
• Solid programming skills in Python, including libraries like pandas, NumPy, scikit-learn, matplotlib, seaborn, and PySpark.
• Experience with Azure (preferred) or AWS, especially in the context of Databricks, data pipelines, and model hosting.
• Good understanding of data warehousing and querying using SQL.
• Familiarity with statistical concepts (e.g. experiment design, hypothesis testing, p-values).
• Strong communication and stakeholder management skills, including the ability to present technical insights to non-technical audiences.
• Fluency in English (written and spoken);

Nice to have: 

• Experience within the retail and fashion industry.
• Experience within international environments, consultancies, or a start-up environment.