Basic
Intermediate Data Scientist - Hiring Now
Posted: 18.05.2026
Closing date: 02.07.2026
Job reference: bd3ceef1d0c70ffcd2fbf3fa9489d204
Job information
Location
Lisboa, Portugal
Company
Jobio
Client / Employer
Imaginary Cloud
Job reference
bd3ceef1d0c70ffcd2fbf3fa9489d204
Listing type
Basic
EU work permit required
No
Posted
18.05.2026
Closing date
02.07.2026
Job description
We are on the lookout for a hardworking Intermediate Data Scientist to join our incredible team at Imaginary Cloud in Portugal.Growing your career as a Full Time Intermediate Data Scientist is a fantastic opportunity to develop excellent skills.If you are strong in leadership, project management and have the right experience for the job, then apply for the position of Intermediate Data Scientist at Imaginary Cloud today! If you're passionate about technology and ready for a challenge, join our team of talented individuals and show your technical skills, creativity, and drive for impact. You'll work with the best in the industry in a supportive, happy, and human-centric environment, making seamless technology. That’s why we were recognized as Best Workplace® in Europe (medium companies), Best Quality of Life Company® and the 2nd Best Great Place to Work® in Portugal by Great Place to Work®. See for yourself by checking our Glassdoor reviews . What exciting projects will you have to make an impact and work on? At Imaginary Cloud, our work improves and simplifies people's lives by creating easy and intuitive digital products. Our day-to-day tasks include development, problem-solving, management, and human interaction. Together, we will drive innovation by creating innovative projects for some of the best companies around the world. You'll be able to grow as you engage with multidisciplinary teams, multiple industries, and projects, overcoming the many challenges that will test and build your skills. Here's an overview of the technical skills you'll likely have to embark on our team: 2+ years of working experience in Data Science Academic background in Computer Science, Statistics, Applied Math, or related field A graduate degree in Data Science or another quantitative field is a plus Good proficiency in common Data Science toolkits, such as R, Python, data processing, database programming, and data analytics Analytical mind with a strong problem-solving aptitude Experience collaborating with engineering and product development teams Fluency in English, both spoken and written We seek team members who live in Portugal or are willing and legally qualified to live and work there The salary range for this position is 30 072,00€ - 36 516,00€ gross per year. Get to know our tech stack: Python / Django Javascript (React.js, Angular.js, Vue.js, Node.js) Ruby / Ruby on Rails Git SQL (MySQL / PostgreSQL) Mobile development (iOS, Android, React Native) Linux / Mac OS - command line Automated provisioning tools (Docker / Ansible / Capistrano) NoSQL (Mongo, Redis, etc.) Photoshop / Figma We want you to feel comfortable here. Get the best of your potential with our benefits: Salary according to your experience and performance Paid sick days Health and dental insurance Comfort budget What you get: A remote-first company Flexible working hours Global projects with industry-leading clients A human-centric culture that values people and empowers them Informal environment Team events to share knowledge and celebrate collectively Mentoring and performance appraisals for solid growth potential Does this sound exactly like what you’re looking for? Then apply now, and let's get the conversation started! Benefits of working as a Intermediate Data Scientist in Portugal:● Company offers great benefits ● Company offers career progression opportunities● Attractive package
Skills
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