Junior Data Scientist

Softlanding; Porto; Híbrido; EUR 35.000 - 60.000; Jornada completa

Descripción de la vacante

Softlanding is launching a Tech Hub in Porto and seeking a data science-focused professional to engineer data features, develop ML models, and analyze experiments for fintech and mobility services.

You’ll translate business questions into analytical solutions, document methodologies with governance, and present insights to cross-functional teams. Strong Python/SQL skills and exposure to modern ML tooling are required.

Formación

• Strong knowledge of Python (Pandas, NumPy, Scikit-learn), SQL, and data visualisation tools.
• Familiarity with machine learning, statistical analysis, and data-driven problem solving.
• Experience with Spark, Databricks, Snowflake, Azure ML, causal inference, NLP, or deep learning is a plus.
• Strong analytical mindset and ability to translate data into actionable insights.

Responsabilidades

• Explore, prepare, and engineer data features for analytics and AI use cases.
• Develop and validate statistical and machine learning models for business problems (pricing, churn, fraud, credit risk).
• Analyse experiments and A/B tests using established methodologies.
• Document models, analyses, and assumptions per governance standards.
• Present insights and recommendations to technical and business stakeholders.
• Mentor peers, participate in code reviews, and continue learning.

Conocimientos

Python

SQL

Data visualization

Pandas/NumPy/Scikit-learn

Herramientas

Spark

Databricks

Snowflake

Azure ML

NLP

Deep learning

Descripción del empleo

You’ll have the opportunity to collaborate with a leading European mobility services provider, headquartered in Germany and backed by nearly 90 years of expertise. As part of this journey, you’ll contribute to the launch of a new Tech Hub in Porto, helping to drive innovative, technology-led solutions that are transforming how businesses move while contributing to a more sustainable future.

YOUR ROLE

• Explore, prepare, and engineer data features for analytics and AI use cases.
• Develop and validate statistical and machine learning models for business problems such as pricing, churn, fraud, and credit risk.
• Analyse experiments and A/B tests following established methodologies.
• Document models, analyses, and assumptions in line with governance standards.
• Present insights and recommendations to technical and business stakeholders.
• Continuously develop skills through mentoring, code reviews, and training.
• Good knowledge of statistics, probability, hypothesis testing, and experimental design.
• Understanding of machine learning techniques, model evaluation, feature engineering, and model validation.
• Ability to translate business questions into analytical solutions.
• Awareness of Explainable AI and Responsible AI principles.
• Interest or experience in fintech, payments, fraud, credit risk, pricing, or mobility services (nice to have).

YOUR PROFILE

• Strong knowledge of Python (Pandas, NumPy, Scikit-learn), SQL, and data visualisation tools.
• Familiarity with machine learning, statistical analysis, and data-driven problem solving.
• Experience with Spark, Databricks, Snowflake, Azure ML, causal inference, NLP, or deep learning (nice to have).
• Strong analytical mindset with the ability to translate data into actionable insights.
• Excellent communication and collaboration skills, with experience working across teams.
• Curious, proactive, and eager to learn within Data Science and AI environments.
• High attention to detail, ownership mentality, and commitment to delivering quality results.Adaptable and comfortable working in fast-paced, evolving environments.
• Personal, academic, or open-source Data Science projects (e.g., GitHub portfolio) (nice to have).
• Strong English (international working environment).