Основы
Data Scientist
Опубликовано: 22.05.2026
Дата закрытия: 06.07.2026
Рекомендация по вакансии: 8233fee507a842addecbc0563c5932b1
Информация о вакансии
Расположение
Bucuresti, Romania
Компания
Jobio
Клиент / Работодатель
Fintech Os Srl
Рекомендация по вакансии
8233fee507a842addecbc0563c5932b1
Тип листинга
Основы
Требуется разрешение на работу в ЕС
Нет
Опубликовано
22.05.2026
Дата закрытия
06.07.2026
Описание должности
Who We Are in a NutshellHi, we are FintechOS! We are the global leader in fintech enablement, on a mission to make fintech innovation accessible to every company. The FintechOS platform simplifies and accelerates the launch, servicing, and expansion of financial products and services - helping businesses realize value up to ten times faster than traditional approaches.With FintechOS, banks, insurance providers, and companies can roll out new financial solutions in as little as 12 weeks.Unlike other financial technologies, FintechOS liberates data from the core, enabling the creation of personalized, differentiated products and customer journeys at scale. As a cloud-native platform, FintechOS integrates with any technology or service financial and non-financial - seamlessly connecting with existing and legacy systems.About the RoleAs a Data Scientist at FintechOS, you will work with large and complex datasets to generate insights that shape business decisions and drive innovation. You will be responsible for developing predictive models, optimizing data processes, and implementing advanced analytics techniques to improve our customers' financial solutions.What You’ll Be DoingWork with large datasets to extract meaningful insights that impact business decisions for our customers.Analyze and interpret data using statistical techniques, providing actionable insights and ongoing reports.Develop and implement data models and machine learning algorithms to enhance predictive capabilities.Assist in designing and maintaining scalable and efficient databases using Google BigQuery.Collaborate with cross-functional teams to understand business requirements and translate them into data-driven solutions.Ensure data integrity, quality, and governance, documenting processes and implementing best practices.Stay up to date with advancements in data science, AI, and analytical techniques to continuously improve our capabilities.Communicate findings and recommendations effectively to both technical and non-technical stakeholders.What You’ll NeedBachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.Certification in Data Science, Data Analytics, or Machine Learning is highly desirable.Proficiency in Python and experience using Jupyter Notebook for data analysis.Hands-on experience with Google BigQuery for data manipulation, storage, and analysis.Strong analytical and problem-solving skills, with the ability to collect, organize, analyze, and interpret large datasets.Knowledge of statistical modeling, machine learning algorithms, and data visualization techniques.Experience with data engineering practices, including ETL processes and database optimization, is a plus.Excellent communication skills with the ability to translate complex data into business insights.Ability to thrive in a fast-paced, dynamic environment, demonstrating adaptability and a customer-oriented mindset.Our CultureWe are a highly motivated team tackling one of the biggest technical challenges in the financial industry. The impact of our work reaches millions worldwide.At FintechOS, we strive to create a diverse, inclusive, and equitable workplace where talented individuals thrive and grow.We are committed to fostering a culture that values diversity across race, gender, sexual orientation, religion, ethnicity, and all unique traits that make us different.Quick FactsVenture-backed business with co-headquarters in New York and London.Serving customers across North America and Europe.Clients range from global leaders like Groupe Société Générale, Admiral Group, and BPCE Oney, to innovative disruptors like Vibrant, eMag, and Howden.Strong partnerships with Deloitte, EY, PWC, and niche consulting agencies.
Навыки
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