Básico
Senior Data Scientist
Publicado: 22.05.2026
Data de encerramento: 06.07.2026
Referência de emprego: 934848b5a45a11e21c03b7f0661cfd4b
Informação do emprego
Localização
Lisboa, Lisbon Metropolitan Area, Portugal
Empresa
Jobio
Cliente / Empregador
Powertalent
Referência de emprego
934848b5a45a11e21c03b7f0661cfd4b
Tipo de listagem
Básico
É necessária autorização de trabalho da UE
Não
Publicado
22.05.2026
Data de encerramento
06.07.2026
Descrição do cargo
PowerTalent: Recruitment, Selection, and Global OutsourcingPowerTalent stands out for its customized talent solutions. As specialists in recruitment and selection, we streamline complex processes and find the best professionals worldwide.We offer recruitment, outsourcing, and hybrid solutions, building local, nearshore, or offshore teams according to our clients’ needs.With PowerTalent, we guarantee complete and efficient solutions, so our clients don’t have to worry about a thing.New opportunity for a new international Tech Hub emerging from Lisbon.We are seeking an experienced Senior Data Scientist to contribute to the design and execution of advanced analytical and machine learning solutions. This exciting role requires a strategic thinker who can link technical decisions to business objectives, mentor teams, and drive high-quality decision-making across cross-functional groups. 5+ years of professional experience in data science environments with proven success in building and architecting production-level data solutions.Advanced Python for ML/DL (NumPy, pandas, scikit-learn, PyTorch/TensorFlow).Strong background in statistics, experimental design, and causal inference.Proven ability to develop and scale complex ML/DL models for production environments.Proficiency in ML experimentation and tracking tools (MLflow, W&B, Databricks ML).Advanced SQL expertise for large-scale data manipulation and workloads.Deep understanding of MLOps workflows (model registry, deployment, monitoring, drift management, retraining).Experience leveraging big-data platforms (Spark, Databricks) to optimize model training and scoring.Solid knowledge of cloud-based ML platforms such as Azure ML, SageMaker, or Vertex AI.Degree in Mathematics, Computer Science, Machine Learning, or a related field.English proficiency (minimum B2 level). Soft Skills:Ability to evaluate trade-offs and articulate sound technical choices.Effectively translate complex technical concepts to non-technical audiences.Exceptional mentoring skills to uplift mid/junior engineers and enforce standards and collaborative practices.Strong aptitude for breaking down ambiguous challenges into actionable, executable solutions.Ownership-minded approach to anticipate and resolve issues while driving long-term platform evolution.Advanced proficiency in data visualization and storytelling tailored for executive-level audiences.Skilled at establishing and mentoring teams to uphold best practices and technical excellence. Contract or B2B, its up to youWork model: 2 days per week in the office and 3 days at home.Continuing education and professional development
Competências
apply blended learning
apply for research funding
apply research ethics and scientific integrity principles in research activities
build recommender systems
Business Analytics
Business Intelligence
collect ICT data
communicate with a non-scientific audience
Computational Biology
Computer Simulation
conduct research across disciplines
create data models
Data Engineering
data ethics
Data Mining
Data Models
data quality assessment
Data Science
data visualisation software
define data quality criteria
deliver visual presentation of data
demonstrate disciplinary expertise
design database in the cloud
design database scheme
develop data processing applications
develop professional network with researchers and scientists
Digital Curation
disseminate results to the scientific community
draft scientific or academic papers and technical documentation
empirical analysis
establish data processes
evaluate research activities
execute analytical mathematical calculations
Hadoop
handle data samples
Healthcare Analytics
image recognition
implement data quality processes
increase the impact of science on policy and society
information categorisation
Information Extraction
integrate gender dimension in research
integrate ICT data
interact professionally in research and professional environments
interpret current data
LDAP
LINQ
make data-driven decisions
manage data
manage data collection systems
manage findable accessible interoperable and reusable data
manage ICT data architecture
manage ICT data classification
manage intellectual property rights
manage open publications
manage personal professional development
manage research data
Marketing Analytics
mathematical modelling
MDX
mentor individuals
multidisciplinary research
N1QL
normalise data
online analytical processing
operate open source software
perform data cleansing
perform data mining
perform project management
perform scientific research
promote open innovation in research
promote the participation of citizens in scientific and research activities
promote the transfer of knowledge
publish academic research
quantitative analysis
query languages
report analysis results
Research Design
resource description framework query language
Scientific Computing
scientific literature
Social Network Analysis
SPARQL
speak different languages
State Estimation
statistical modeling techniques
Statistics
synthesise information
teach in academic or vocational contexts
think abstractly
Unstructured Data
use data processing techniques
use databases
use spreadsheets software
visual presentation techniques
write scientific publications
XQuery