Data Science Associate (Fashion) Porto

Data Science Associate (Fashion)
Porto
Porto, Porto District, Portugal

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

Who we are

We are Metyis, a
- 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
- 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, e
Commerce and technology capabilities of the company and boosting digital sales. The HUGO BOSS Digital Campus employees will help create a
-
-
- art data architecture infrastructure, advanced business analytics, and the development and enhancement of HUGO BOSS’ e
Commerce 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
- 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
  - 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
  - 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, Git
  L).
• Leverage Databricks, Azure, or similar cloud infrastructure for scalable data processing and model deployment.
• Use Python, Py
  Spark, and common ML libraries (e. G.
  - learn, XGBoost, Light
  GBM, 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
  - functional stakeholders (e. G. Business teams, Data Engineering, IT teams) and contribute to
  - 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
  - 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, Num
  Py,
  - learn, matplotlib, seaborn, and Py
  Spark.
• 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,
  - values).
• Strong communication and stakeholder management skills, including the ability to present technical insights to
  - 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
- up environment.

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