Senior Data Science Engineer
π§ Tech Level: Senior
π£ Language Proficiency: Upper-Intermediate
π₯ FTE: 1
π§Ύ Employment type: Full time
π Candidate Location: Poland β preferred, Europe β possible
π Working Time Zone: CET
π Start: ASAP
π§ Planned Work Duration: 6 months
π₯ Customer Description:
A global mobility and urban services platform that allows users to book rides or other services and negotiate the fare directly with the service provider. It offers a variety of services including ride-hailing, intercity travel, delivery, and task assistance, operating globally across multiple cities and countries.
π§© Project Description:
Incidents detection, image/audio analysis.
βοΈ Project Phase: New phase of the project
π€ Soft Skills:
β’ Highly proactive β ability to figure out who to reach out to and how to get things done independently.
β’ Stakeholder management β comfortable interacting with various stakeholders, from senior developers to product managers.
β’ Curious mindset β challenges existing processes and looks for continuous improvement.
β’ Strong communication β able to have project-related conversations with product managers and other team members.
β’ Time management β organized and reliable.
π‘ Hard Skills / Must Have:
β’ 5+ years of professional experience in a Data Science or Machine Learning role. Previous software engineering experience is preferrable. An academic background in a quantitative field such as Computer Science, Mathematics, or a related discipline will be a plus
β’ Expert-level proficiency in Python and its core data science libraries (e.g., Pandas, NumPy, Scikit-learn).
β’ Deep expertise in classic machine learning and deep learning techniques, with a strong understanding of advanced mathematics relevant to these fields.
β’ Experience with ML system design and MLOps practices for building, testing, deploying, and monitoring models in a production environment.
β’ Proven experience with event systems, deployment environments, and maintaining production services.
β’ Familiarity with technologies for streaming, batch, and async data processing.
β’ Proficiency in at least one specialized ML domain, such as Computer Vision (CV) or Natural Language Processing (NLP).
β’ Strong understanding of software system design principles and the ability to contribute to architectural discussions.
β’ Experience in experimental design to validate hypotheses and measure the effectiveness of solutions.
β’ A solid grasp of security, risk, and control concepts in a production environment.
β’ Russian language is a must.
π Responsibilities and Tasks:
β’ Lead the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance
β’ Translate complex business goals into well-defined Data Science problems and quantifiable metrics
β’ Design and develop robust, scalable Machine Learning systems from scratch, including data analysis, annotation, and processing pipelines
β’ Contribute to the overall system architecture and integrate ML models with existing backend services and infrastructure
β’ Monitor and maintain deployed models, proactively identifying and addressing issues like concept drift to ensure consistent performance
β’ Support the development and growth of other team members through mentorship and participation in onboarding programs
β’ Drive continuous improvement by automating repetitive tasks and proposing innovative solutions that lead to significant business impact
β’ Communicate complex technical concepts and findings clearly and concisely to both technical and non-technical stakeholders
π§ͺ Technology Stack: Python, Pandas/NumPy/Scikit-learn, CV, NLP
π© Ready to Join?
We look forward to receiving your application and welcoming you to our team!
- Department
- Data Engineering
- Locations
- Poland, Spain
- Remote status
- Fully Remote
About Bonapolia
For job seekers, BONAPOLIA offers a gateway to exciting career prospects and the chance to thrive in a fulfilling work environment. We believe that the right job can transform lives, and we are committed to making that happen for you.