मूलवर्ती

Data Scientist

Bucuresti, Romania अतिथि: Jobio ग्राहक/नियोक्ता: Fintech Os Srl
नियुक्त: 22.05.2026
अंतिम तिथि: 06.07.2026
नौकरी का संदर्भ: 8233fee507a842addecbc0563c5932b1

नौकरी की जानकारी

स्थान
Bucuresti, Romania
अतिथि
Jobio
ग्राहक/नियोक्ता
Fintech Os Srl
नौकरी का संदर्भ
8233fee507a842addecbc0563c5932b1
लिस्टिंग प्रकार
मूलवर्ती
यूरोपीय संघ के वर्क परमिट की आवश्यकता है
नहीं
नियुक्त
22.05.2026
अंतिम तिथि
06.07.2026

नौकरी का विवरण

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.

कौशल

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

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