Junior Data Scientist

Junior Data Scientist at Northius

At Northius, our mission is to offer an educational platform focused on people's employability. We are a company where sustainability and social commitment are fundamental pillars. We serve over 40,000 students annually and have 12,000 agreements with companies.

Since 2023, we have been building an internal Product, Engineering, and Data (PED) team to transform Northius into an EdTech company with its own digital product.

Business Context

Northius operates more than 10 training schools, each focused on a specific professional sector: CEAC, Deusto Formación, Deusto Salud, Campus Training, Unisport, CEMP, Mint, CEAC FP, Tokio School, 35mm, Nubika, Flou, Wiikon, and Vibe.

In 2019, an investment fund consolidated the group's expansion, enabling us to reach a turnover of 100M€ in 2022, with over 40 physical delegations in Spain and Portugal, and selling our training programs across Europe and Latin America.

The Challenge: Becoming an EdTech Company

In terms of Digital Product, we have everything to build. To date, we have invested in school portals (Wordpress), the sales platform (Salesforce), learning platforms (Moodle and DNN), and the billing platform (Business Central).

Our Data Science team is responsible for tackling predictive modeling and generative AI projects that can have the greatest business impact. We work directly with business and product teams to understand core problems and address them collaboratively. We aim to build the educational platform of the future to solve our students' employability challenges, and this requires revolutionizing the current model.

Technological Stack

Within the Data team, we utilize a Datalake built on AWS cloud, which ingests data from our platforms and transforms it to provide a knowledge layer, facilitating data visualization and reliable decision-making.

We structure data into three layers (Bronze, Silver, and Gold). Prefect is used for orchestrating all data extraction processes, and DBT defines the data schemas for each layer.

We deploy our ML models on AWS Sagemaker. For generative AI, we use various providers, primarily OpenAI.

Our Values

We believe that a team is more than the sum of its members, and that a high-performing team requires effective collaboration. Just as the Manifesto for Agile Software Development guides us in building software, our Manifesto for Product Engineers serves as a reference for our collaboration and teamwork:

• Versatile engineers over highly specialized individuals
• Adding value to our product over adding value to our tech stack
• Rock solid over Rock star
• In production over "my part is done"
• Problem solvers over problem risers
• Feedback loop over hierarchy rules

We are looking for a Junior Data Scientist to join our Product, Engineering, and Data (PED) team. If everything you've read so far motivates you and you consider yourself a developer focused on contributing value to the product, keep reading!

What will be your responsibilities?

• Implementation of predictive models: Understand the business problem and implement the minimum viable solution to address the business problem or stakeholder need.
• Implementation of generative AI solutions: Create tools to help our students gain knowledge faster or require less support, ensuring solution consistency and quality.
• Data Architecture: Participate in designing the data model within the Data Guild.
• Product Orientation: Understand business problems and drive a Data-Driven culture in product decision-making.
• Technical Leadership: Perform data analysis to draw conclusions that improve the product, collaborating with Engineering teams.

What we offer you

• Permanent contract, full-time.
• 100% remote in Spain.
• Offices in A Coruña, Madrid, and Barcelona, if you wish to work with others.
• 23 days of vacation.
• Continuous workday on Fridays and holiday eves throughout the year.
• Continuous workday in summer.
• Flexible hours.
• Necessary equipment for comfortable work.
• Access to Flexible Remuneration program: Health Insurance, Gourmet Voucher, Transport Card, Daycare, shopping club, and discounts on health services.

Who you will work with

At Northius, we have over 1000 employees, but the Product, Engineering, and Data team was just created in 2023. These are some of the people who lead it and with whom you would work daily:

• Alberto Baselga (CIO/CPO): Ex-Coverwallet and passionate about product ecosystems. Startup Advisor and Investor with a career focused on high-impact digital companies.
• Daniel Ruiz (Head of IA): Ex-Cabify and Ex-Coverwallet, over 7 years of experience in artificial intelligence, designing high-impact business models.
• Pablo Moreno (Data Science Tech Lead): Ex-BBVA, over 6 years of experience creating data products to impact business.
• Alcibiades Cabral Díaz (Head of Engineering): Ex-Santander, over 10 years of experience leading teams with a servant leadership approach to achieve high performance and build incredible products.
• Juan Barrero López (Staff Engineer): Over 10 years of experience in software engineering across various sectors, providing technical solidity and architectural vision. A reference for design decisions and building scalable, maintainable solutions.
• Jose Manuel Montilla (Junior Data Scientist): Mathematician and Physicist with a strong analytical foundation. Started as a Data Scientist intern at Northius and quickly demonstrated his ability to add value, consolidating as a Junior Data Scientist with great projection.
• Maria Elena García García (Senior Data Scientist): Ex-Telefónica, over 10 years of experience applying artificial intelligence in various sectors. Combines technical expertise with teaching, making her key in understanding business needs.
• Santiago Arroyo Marioli (Senior Data Scientist): Over 9 years of experience developing high-impact data solutions in multiple industries. His hybrid profile in finance and teaching background allow him to navigate the company with ease, especially in the financial sector.
• Axel Cabrera Rodríguez (Senior Data Scientist): Ex-BBVA, over 7 years of experience building machine learning models in highly demanding regulatory and scale environments. Brings a product-oriented and data-driven decision-making vision.

What we ask of you

• 0–1 years of experience (internships, first job, or relevant projects) in Data Science / Analytics / ML.
• Positive and proactive attitude towards teamwork, new technologies, and ways of working.

Foundations:

• Proficient in Python for analysis (pandas, numpy) and regular work with Jupyter notebooks.
• Practical knowledge of SQL (queries, joins, aggregations).
• Ability to understand a business problem, translate it into measurable hypotheses, and propose a simple analysis or solution.
• Familiarity with model concepts (classification/regression), basic metrics, and validation (even at a training/project level).
• Experience with LLMs (OpenAI or others) in a project, demo, or practical case: prompts, basic evaluation, error handling.
• Basic knowledge of working with Git (GitHub, etc.).

Team Success:

• Comfortable working in a team: asking for help, sharing progress, and documenting your work.
• Clear communication oriented towards collaboration (technical and non-technical stakeholders).
• Knowledge of agile environments and iterative work. Preferably academic experience.

Deliver value:

• Impact mindset: prioritize delivering something useful (MVP) and improving it with feedback and data.
• Ability to manage uncertainty, decompose problems, and propose next steps.

Accountability:

• Take responsibility for your tasks, provide visibility of progress and blockers.
• Interested in receiving and giving constructive feedback.

It's a plus if you also...

• Know DBT as a data transformation tool.
• Have a passion for education and technology, and their intersection.
• Have done projects in EdTech / e-learning or understand (even at a high level) how platforms like Moodle work.

Selection Process

The selection process aims to evaluate if you fit into one of the PED squads as a Data Scientist. It's important that you ask any questions you need to determine if Northius is a good fit for you too. If we hire you, we want it to be for the long term.

We use the STAR methodology. You will have an HR person who will guide you through the process:

1. Interview with HR.
2. Technical interview.
3. Technical test.
4. Product interview.

In all interviews, you will have 15 minutes at the end to ask any questions you deem necessary to understand what your day-to-day would be like if you join the team.

Equal opportunities and diversity within the team, as well as promoting labor inclusion, are some of our commitments. Additionally, all our job offers consider people with disability certificates.

Key skills/competency

• Python (Pandas, Numpy, Jupyter)
• SQL
• AWS
• Sagemaker
• Generative AI
• Large Language Models (LLMs)
• Data Modeling
• Predictive Models
• Git
• Agile Methodologies