Data Scientist – ML & Optimisation models

Aktios Spain; Viladecans; Híbrido; EUR 40.000 - 70.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Health insurance

Transportation vouchers

Restaurant vouchers

Childcare vouchers

Access to gyms and sports centers

Descripción de la vacante

Aktios Spain is looking for a Senior Data Scientist to design and implement advanced analytics solutions in the aviation sector. This role involves developing machine learning models and decision-support software, contributing to the entire value chain of software products.

Candidates should have a Master's degree or equivalent experience, strong Python skills, and a solid understanding of machine learning techniques. The position offers opportunities for professional growth and a flexible compensation package.

Formación

• Master's degree or greater in data science, ML, or operational research, or 2+ years of highly relevant industry experience.
• Strong knowledge of supervised and unsupervised machine learning techniques.
• 0-2 years working on production ML or optimization software products.

Responsabilidades

• Design and implement advanced analytics solutions.
• Develop industrialized machine learning and optimization models.
• Engage with business stakeholders to collect requirements and get feedback.

Conocimientos

Machine learning techniques

Optimization techniques

Fluency in Python

Data visualization

Analytical skills

Educación

Master's degree in data science, ML, or operational research

Herramientas

scikit-learn

pandas

AWS

Git

Docker

Descripción del empleo

We are seeking a Senior Data Scientist to design and implement advanced analytics solutions for a leading aviation-sector organization. This role is responsible for developing industrialized optimisation and machine learning models as part of a fullstack product squad that delivers operations decision‑support software.

We are a team of over 180 professionals passionate about what we do, working hand in hand on every project. Our individuals are part of a multidisciplinary environment where cooperative work is the key to our success. We are committed to ensuring a professional career by designing the evolution of knowledge and responsibilities. We collaborate with leading companies in innovation, learning from them and discovering new perspectives.

What will the day‑to‑day look like?

The Data Scientist has full‑stack accountabilities across the full value chain of building an industrialized data‑science software product:

Understanding a business problem and its component processes end to end, and identifying opportunities to make decisions more optimally leveraging decision‑support tooling.

Efficiently conducting analyses and visualisations to identify valuable opportunities for decision‑support and to determine trade‑offs between different potential feature implementations.

Prototyping advanced machine learning and optimisation models to prove the value of a use case and approach (in Python).

Delivering features to industrialise machine learning and optimisation models in Python using best‑practice software principles (e.g., strict typing, classes, testing).

Building automated, robust data cleaning pipelines that follow software best practices (in Python).

Implementing integrations between the core algorithm (machine learning or optimisation) and a workflow orchestration paradigm such as Dagster.

Implementing software in a cloud‑based deployment pipeline with Continuous Integration / Continuous Deployment (CI/CD) principles.

Building logging, error handling, and automated tests (e.g., unit tests, regression tests) to ensure the robustness of operationally critical decision‑support products.

Delivering features to harden an algorithm against edge cases in the operation and in data.

Conducting analysis to quantify the adoption and value capture from a decision‑support product.

Engaging with business stakeholders to collect requirements and get feedback.

Contributing to conversations on feature prioritisation and roadmap, with an understanding of the trade‑off between speed vs. long‑term value.

Understanding and integrating the product into existing business processes, and contributing to the development and adoption of new business processes leveraging a decision‑support product.

Communicating feature and modelling approach, trade‑offs, and results with the internal team and business stakeholders.

The Data Scientist is also accountable for ways of working fit for an Agile cross‑functional development squad, including:

Using Git versioning best practices for version control.

Contributing to and reviewing pull requests and product/technical documentation.

Providing input on prioritisation, team process improvements, and optimising technology choices.

Working independently and providing predictability on delivery timelines.

What are we looking for?

Technical Skills

Strong knowledge of either machine learning and optimisation techniques, incl. supervised (regression, tree methods, etc.), unsupervised (clustering) learning, and operations research (linear, mixed integer programming, heuristics).

Fluent in Python (required) and other programming languages (preferred) with strong skills in applying DS, ML, and OR packages (scikit‑learn, pandas, numpy, Gurobi etc.) to solve real‑life problems and visualise the outcomes (e.g., seaborn).

Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (e.g., MLflow).

Experience with cloud‑based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker, ECS) nice to have.

Experience in code testing (unit, integration, end‑to‑end tests).

Advanced analytical skills, including the ability to apply a range of data science and analytic techniques to quickly generate accurate business insights.

Understanding of the trade‑offs of different data science, machine learning, and optimisation approaches, and ability to intelligently select which are the best candidates to solve a particular business problem.

Able to structure business and technical problems, identify trade‑offs, and propose solutions.

Communication of advanced technical concepts to audiences with varying levels of technical skills.

Managing priorities and timelines to deliver features in a timely manner that meet business requirements.

Collaborative team‑working, giving and receiving feedback, and always seeking to improve team processes.

Master's degree or greater in data science, ML, or operational research, or 2+ years of highly relevant industry experience (required).

0–2 years working on production ML or optimisation software products at scale (required).

Experience in developing industrialised software, especially data science or machine learning software products (preferred).

Experience in relevant business domains (transportation, airlines, operations, network problems) (preferred).

What can we offer you?

• Opportunity for professional development in a technological and innovative international environment.
• Working hours: 09:00 to 17:00.
• You will be part of a pleasant and challenging work environment, surrounded by colleagues who will support you in overcoming challenges within the projects where you will grow.
• We provide professional growth opportunities with individualized career plans aligned with training and certifications covered by the company, designed for your professional and personal development.
• Flexible compensation (health insurance, transportation vouchers, restaurant vouchers, and childcare vouchers) and access to a network of gyms and sports centres at a special rate through the company.
• Being part of a company that advocates for equality and diversity.