Data Science Engineer

Aether Biomedical; Deutschland; Vor Ort; EUR 90.000 - 130.000; Vollzeit

Benefits dieser Stelle

Remote work options

Hybrid/Office flexibility

Private health insurance

Zusammenfassung

Andersen is seeking a Data Science Engineer to build an AI platform for incident detection using computer vision, audio analysis, and multimodal ML. You will lead the full ML lifecycle from research to production, translating business goals into concrete data science problems and metrics.

You will design scalable ML systems, collaborate with backend teams, and monitor deployed models. Expect mentorship responsibilities, and a flexible work setup with remote, office, or hybrid options.

Qualifikationen

• 5+ years in data science or ML roles.
• Clear ability to translate business goals into DS problems.
• Strong foundations in ML/DL and mathematics.
• Experience with production ML systems and monitoring.
• Comfort with designing experiments to validate solutions.

Aufgaben

• Lead the full ML model lifecycle from research to production deployment.
• Translate business goals into measurable DS objectives and metrics.
• Design robust, scalable ML systems including data pipelines and annotations.
• Integrate ML models with backend services and infrastructure.
• Monitor models and address issues like drift; mentor teammates.

Kenntnisse

Python

Pandas

NumPy

Scikit-learn

Deep learning

ML system design

English Intermediate+

Ausbildung

Master's or PhD in CS/Math or related

Tools

MLOps

Kafka

Jobbeschreibung

Andersen is hiring a Data Science Engineer for a project building an AI platform for incident detection using computer vision, audio analysis, and machine learning. The customer is an international mobility service provider offering a peer-to-peer model that allows users to negotiate travel conditions directly within the app. With a large global user base and operations spanning numerous cities worldwide, the organization is recognized for its focus on flexibility, accessibility, and the adaptation of its platform to diverse market environments. The project is focused on building an AI-driven incident detection platform that automatically identifies, classifies, and escalates safety-related events. It leverages computer vision, audio analysis, and multimodal machine learning to ensure timely and accurate incident recognition.

Responsibilities

• Leading the entire machine learning model lifecycle, from initial research and hypothesis testing to production deployment and maintenance.
• Translating complex business goals into well-defined data science problems and quantifiable metrics.
• Designing and developing robust, scalable machine-learning systems from scratch, including data analysis, annotation, and processing pipelines.
• Contributing to the overall system architecture and integrating ML models with existing backend services and infrastructure.
• Monitoring and maintaining deployed models, proactively identifying and addressing issues like concept drift to ensure consistent performance.
• Supporting the development and growth of other team members through mentorship and participation in onboarding programs.
• Driving continuous improvement by automating repetitive tasks and proposing innovative solutions that lead to significant business impact.

Must-haves

• Experience in a data science or machine learning role for 5+ years.
• Experience communicating complex technical concepts and findings clearly to both technical and non-technical stakeholders.
• Expert-level proficiency in Python and core data science libraries (Pandas, NumPy, Scikit-learn).
• Deep expertise in machine learning and deep learning techniques, including 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 the 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.
• Experience in software engineering (preferred).
• Experience working with production systems and maintaining live services.
• Deep knowledge of machine learning and deep learning techniques.
• Expertise in a specialized ML domain (Computer Vision or Natural Language Processing).
• Level of English – from Intermediate+ and above.

Nice-to-haves

• Experience with ML system design and MLOps practices (building, testing, deploying, monitoring models in production).
• Academic background in Computer Science, Mathematics, or a related quantitative field.
• Experience with ML system design and MLOps practices in production environments.
• Expertise in a specialized ML domain (Computer Vision or Natural Language Processing).

Reasons why this job would be interesting to you

• Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others.
• Andersen cooperates with such businesses as Samsung, Siemens, Johnson & Johnson, BNP Paribas, Ryanair, Mercedes, TUI, Verivox, Allianz, T-Systems, etc.
• The opportunity to change the project and/or develop expertise in an interesting business domain.
• Job conditions – you can work both fully remotely and from the office or can choose a hybrid variant.
• Guarantee of professional, financial, and career growth!
• The company has introduced systems of mentoring and adaptation for each new employee.
• The opportunity to earn additional up to 1,000 USD per month by participating in the company's activities.
• Access to the corporate training portal, where the entire knowledge base of the company is collected and which is constantly updated.
• Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies).
• Certification compensation (AWS, PMP, etc).
• Referral program.
• English courses.
• Private health insurance and compensation for sports activities.

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