About the Role We are seeking a Data Scientist with
experience to join our Data Science team. This new team member will
play a crucial role in developing data science solutions from
conception to implementation as we continue to enhance the world of
retail and make it more sustainable. At Nextail, we empower
retailers to create better experiences while using fewer of the
world's resources by selling more with less inventory. Nextail’s
cloud-based platform uses artificial intelligence, prescriptive
analytics, and optimization to deliver agile merchandising
decisions. To date, we are working with integral retailers like River
Island, Guess, Flying Tiger or Pepe Jeans. Key Responsibilities
Developing Solutions: contributing to the development of data
science solutions from idea to maturity, with a main focus on
demand forecasting and optimization models. Collaborating: Working
closely with product managers, developers, data engineers, and
business experts to solve end-to-end problems. Applying Techniques:
Utilizing data science techniques including ML, SQL, optimization,




simulation, and visualization to address business challenges.
Learning and Growing: Embracing a culture of continuous learning
and growth, staying up-to-date with the latest methodologies and
best practices in data science. Analyzing and Communicating:
Analyzing and understanding complex data, extracting insights, and
effectively communicating findings to stakeholders. Supporting
Operations: Monitoring models in production, measuring their impact
on the business, and iterating to improve performance over time.
Requirements Experience: at least 3-4 years of experience working
as a data scientist, or in a related field. Education: Background
in computer science or a related field. Programming Skills:
Proficiency in programming languages, Python is a must. Solid
understanding of software engineering best practices, including GIT
and CI/CD. Technologies: Familiarity with tools such as Notebooks,
Databricks,

📌 Data Scientist (Madrid)
🏢 Nextail
📍 Madrid