Data Scientist
- Status
- Open
- Remote policy
- Hybrid
- Employment type
- Not stated
- Salary
- 60,000-70,000 EUR
- Source
- landingjobs
- First observed
- 2026-09-17 09:23 UTC
- Last seen
- 2026-09-17 09:23 UTC
- Source claims posted
- 2026-09-17 09:13 UTC
- Consecutive misses
- 0 of 3
What the posting says
At Damia (Permanent), in Lisbon, Portugal
Salary: €60.000 - €70.000
Expires at: 2027-05-12
Remote policy: Partial remote
About Damia
Damia is a specialist tech recruitment agency in Portugal, focused on technology, product, and engineering roles. We work with funded scaleups, international companies building teams in Portugal, and established tech organisations scaling critical hires.
Our approach is consultative, not transactional. Every mandate runs through a structured methodology, from strategic discovery and talent mapping to curated shortlists and post-hire follow-up, led by senior recruiters who understand the market and the roles they recruit for.
We are part of the Triveris Group ecosystem alongside We Are META and Landing.Jobs, giving us reach across the full spectrum of tech talent in Portugal.
About the role: The Data Science department plays a pivotal role in the company, generating value by developing algorithms and analytical production-grade solutions. The team leverages advanced techniques and algorithms to provide maximum value from data in all shapes and sizes (such as classification models, NLP, anomaly detection, graph theory, deep learning, and more). As a Data Scientist, the successful candidate will assume the classic data science role of an end-to-end project development and implementation practitioner. Being part of the team requires a mix of hard quantitative and analytical skills, a solid background in statistical modeling and machine learning, a technically savvy nature, along with a passion for problem solving and a desire to drive data-driven decision-making.
Responsibilities:
Data Exploration and Preprocessing: Collect, clean, and transform large, complex data sets from various sources to ensure data quality and integrity for analysis
Statistical Analysis and Modeling: Apply statistical methods and mathematical models to identify patterns, trends, and relationships in data sets, and develop predictive models
Machine Learning: Develop and implement machine learning algorithms, such as classification, regression, clustering, and deep learning, to solve business problems and improve processes
Feature Engineering: Extract relevant features from structured and unstructured data sources, and design and engineer new features to enhance model performance
Model Development and Evaluation: Build, train, and optimize machine learning models using state-of-the-art techniques, and evaluate model performance using appropriate metrics
Data Visualization: Present complex analysis results in a clear and concise manner using data visualization techniques, and communicate insights to stakeholders effectively
Collaborative Problem-Solving: Collaborate with cross-functional teams, including product managers, data engineers, software developers, and business stakeholders to identify data-driven solutions and implement them in production environments
Research and Innovation: Stay up to date with the latest advancements in data science, machine learning, and related fields, and proactively explore new approaches to enhance the company's analytical capabilities
Requirements
B.Sc (M.Sc is a plus) in Computer Science, Mathematics, Statistics, or a related field
3+ years of proven experience designing and implementing machine learning algorithms and successfully deploying them to production.
Strong understanding and practical experience with various machine learning algorithms.
Proficiency in Python
Experience with SQL and data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform data for analysis
Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design
Strong analytical and critical thinking skills to approach business problems, formulate hypotheses, and translate them into actionable solutions
Proficiency in data visualization libraries to create meaningful visual representations of complex data
Excellent written and verbal communication skills to present complex findings and technical concepts to both technical and non-technical stakeholders
Demonstrated ability to work effectively in cross-functional teams, collaborate with colleagues, and contribute to a positive work environment
Experience with Big Data tools
Currently living in Portugal and legally authorized to work in the country
Nice to have:
Experience in the fraud domain
Experience with Airflow, CircleCI, PySpark, Docker and K8S
Quality
- + Salary range stated weight 35%
- + Remote policy stated weight 20%
- + Location stated weight 15%
- + Organisation stated weight 15%
- + Publication date stated weight 15%
Not enough history yet to judge honesty signals.
Timeline
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#810523 2026-09-17 09:23 UTCPublished