Data Science Engineer
New
Warszawa, rondo Ignacego Daszyńskiego 1, Belgrad, Trg Nikole Pašića 5, Vilnius, Gedimino pr. 20, chisinau, Strada 31 August 1989 78, Budapest, Klauzál u. 30, Warszawa, Country code: PLFull-TimeMiddle
Salary3700 - 4800 USD per month gross any currencySource=original
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Job Details
- Languages
- Intermediate+ English (B1)
- Experience
- 5+ years
- Required Skills
- PythonMachine LearningNumpyData sciencePandasDeep Learningscikit-learnNLPComputer Vision
Requirements
- 5+ years of experience in a data science or machine learning role.
- Expert-level proficiency in Python and core data science libraries (Pandas, NumPy, Scikit-learn).
- Deep expertise in machine learning and deep learning techniques with strong mathematical foundations.
- Experience with event-driven systems, deployment environments, and maintaining production services.
- Familiarity with streaming, batch, and asynchronous data processing technologies.
- Strong understanding of software system design principles and ability to contribute to architecture discussions.
- Experience in experimental design for hypothesis validation and solution effectiveness measurement.
- Understanding security, risk, and control principles in production environments.
- Expertise in a specialized ML domain (Computer Vision or Natural Language Processing).
- Clear communication of technical concepts to technical and non-technical stakeholders.
- Intermediate+ (B1) level of English.
Responsibilities
- Lead the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance.
- Translate complex business goals into well-defined data science problems and quantifiable metrics.
- Design and develop robust, scalable machine learning systems from scratch, including data analysis, annotation, and processing pipelines.
- Contribute to the overall system architecture and integrate ML models with existing backend services and infrastructure.
- Monitor and maintain deployed models to ensure consistent performance, addressing issues such as concept drift.
- Support team member development through mentorship and participation in onboarding programs.
- Drive continuous improvement by automating repetitive tasks and proposing innovative solutions.
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