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AI Hybrid Remote Full-time Worldwide

Data Scientist

Damia Lisbon, PortugalSalary: €60.000 - €70.000

Looking for a Hybrid Remote AI role? Data Scientist at Damia is listed on Makely Remote Jobs as a Full-time opening based in Lisbon, PortugalSalary: €60.000 - €70.000 (Worldwide). Review the role overview below, then apply on the employer’s original listing — Makely Remote Jobs does not process applications.

Role overview

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

Summary provided for discovery. Always confirm details and apply on the original source. Makely Remote Jobs is not the employer and does not process applications.

Frequently asked questions

Is Data Scientist at Damia a remote job?

Yes. This listing is categorized as Hybrid Remote on Makely Remote Jobs. Confirm any location or timezone limits in the original posting before you apply.

What is the employment type for Data Scientist?

Source data lists this as Full-time. Always verify the contract type, benefits, and start date on the employer’s application page.

Where is Data Scientist located?

Listed location: Lisbon, PortugalSalary: €60.000 - €70.000. Many remote AI roles allow work-from-home with country or timezone restrictions — check the full description.

Do I apply on Makely Remote Jobs?

No. Makely Remote Jobs aggregates public remote job feeds for discovery. Use “Apply on Original Site” to open the employer’s official application URL. We never host applications or collect resumes.

Does Damia list salary for this AI role?

Salary was not published in the source feed. Check the original listing or ask the recruiter during screening for compensation details.