Backend Engineering Intern, Nextail
Retail merchandising platform
Job no longer available
Retail merchandising platform
101-200 employees
Job no longer available
101-200 employees
Company mission
Nextail's mission is to make the fashion retail world a better place by helping retailers to transform their merchandising processes and inventory management through AI-driven tools.
Role
Who you are
- Residence in Spain is required
- You must have the ability to work through an internship agreement (“Convenio”)
- You are fluent in English (other languages, especially Spanish, are a plus) and are interested in working in an international company
- Curiosity and passion for new technologies
- Experience in developing, training, and deploying machine learning models using automated procedures that integrate Data, Development, Security, and Infrastructure teams
- Comfortable working in high-performance computational environments (Apache Spark, Databricks)
- Theoretical and practical experience building pipelines for Data Science teams
- Business-oriented. You acknowledge software is not the end but a means to get business value (but this doesn’t mean doing crappy code). You are willing to learn all business concepts and you try to understand the business motivation under the tasks you develop
- Self-motivated and self-organized. Good time management and personal organization skills are essential
- You value working as a team, receiving feedback, and being willing to learn
What the job involves
- We’re looking for a Backend Engineering Intern for our technical team. This new team member will be instrumental in developing data science solutions from the idea to maturity as we continue to make the retail world a better, more sustainable place
- The goal of the technical and data science teams is to multiply the impact of our product on the business
- Data Science Techniques, AI, ML, Optimisation, Simulation, and Visualization, are the tools we always have at hand when we face a problem, but we will never use them in vain
- We work together with Product Managers, Developers, Data Scientists, ML Engineers, Data Engineers, and Business Experts to solve the end-to-end problem
- Our job is not finished when the model and the end-to-end solution are in production, or after the change management and operational details are closed, not even when we have strong evidence that the solution is solving the user's problem and she is satisfied because after that we continue monitoring our models
- The discussion between pairs, working together, and challenging each other, is the fastest way to solve a problem and to grow as a Machine Learning Engineer
- We have a culture of sharing, transparency, meritocracy, caring, and trusting each other
- You will:
- Participate in the development, deployment, and maintenance of the multiple Machine Learning models they are working with
- Help to instrument the different models that the squad creates, to collect metrics and usage statistics
- Implement mathematical algorithms or complex computations
- Influence the whole model production flow and take part in its improvement process
- Encourage good technical practices in the squad
- Work closely with the Data Science team, helping in the design of their models to ensure they are scalable
Our take
Making merchandising decisions as a fashion business is essential for inventory surplus, increasing sales, and lowering inventory loads. This is relatively simple to achieve based on macro analytics, but automating and anticipating demand at a local level is significantly more challenging.
Nextail provides AI-driven merchandise management solutions for fashion retailers, providing analytics at a hyper-local level to help companies optimize their inventories. Its tools help to predict ideal purchase quantities to reduce leftovers, replenish stock precisely, transfer stock between stores, and engage with actionable data-driven analytics.
Whilst AI-driven merchandising solutions have been on the market for several years, Nextail’s angle of specializing in tackling inventory optimization within the fashion retail industry is a rather unique one. Furthermore, the company has made a smart move by focussing on hyper-local analytics and insights, helping to make a company more profitable at the macro level by focussing on micro efficiencies.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Company
Funding (last 2 of 3 rounds)
Jun 2018
$10.3m
SERIES A
Sep 2016
$1.6m
SEED
Total funding: $12.3m
Company benefits
- Remote-first
- Flexible work hours
- Learning allowance
- Work equipment
- At our main office you enjoy coworking and meeting spaces, outdoor areas, and a fully-stocked kitchen
- Remuneration scheme
- Stock options
Company HQ
El Viso, Madrid, Spain
Leadership
Joaquin Villalba
(CEO)Customer Solutions Manager for Kuehne + Nagel from 2003 to 2007. Head of European Logistics Operations for Inditex from 2008 to 2012.
Carlos Miragall
(Board Member)Experience as Senior Manager of A. T. Kearney from 2008 to 2014. Chief Financial Officer of Panaseer since 2020.
Javier Lafuente
(Board Member (Observer))Founder and Director of Analytical Intelligence for Decide Soluciones. Founder and Head of Product Development for ORQUEST.
Share this job