Job
- Level
- Senior
- Job Feld
- Data
- Anstellung
- Vollzeit
- Vertragsart
- Unbefristetes Dienstverhältnis
- Gehalt
- 80.000 bis 100.000€ Brutto/Jahr
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
Job Zusammenfassung
In dieser Rolle entwickelst du Machine Learning-Modelle zur Betrugsbekämpfung und Compliance, bereitest Trainingsdaten auf, führst Feature Engineering durch, und optimierst Modelle, während du eng mit Stakeholdern und dem Infrastrukturteam zusammenarbeitest.
Job Technologien
Deine Rolle im Team
- Development, operationalisation and maintenance of Machine Learning models in close collaboration with the business stakeholders for common risk and financial protection with different latency: Fraud Protection, Compliance & AML.
- Training data preparation in close collaboration with the analytics engineers including analysis of vast amounts of transactional logs, data labelling, applying chronological splitting and sampling techniques to handle class imbalances.
- Feature engineering operations including common features, cross features, positional features and building a centralised feature store.
- Model selection, experimentation and training of baseline and gradient boosted models, evaluating performance and trade offs.
- Model deployment and prediction servicing from batch to online in close collaboration with the data infrastructure team.
- Continual learning by setting up automated pipelines that monitor population drift and continuously re-fit models on fresh data when performance drops below predefined operational baselines.
- Knowledge sharing and mentoring across the team.
Unsere Erwartungen an dich
Ausbildung
- Degree in Computer Science, Applied Mathematics, Statistics, Quantitive Finance and targeted Financial Engineering courses.
Qualifikationen
- Proficiency in data science libraries (pandas, polars, numpy, scikit-learn) and gradient boosting frameworks (XGBoost).
- Good knowledge of data transformation and data orchestration tools, ideally dbt and airflow.
- Solid understanding of software engineering principles, including version control (Git), CI/CD, and automated testing.
- Payment, Fraud and Risk Domain Expertise: Understand transactions movement, payment payload and authentication protocols. Recognize differences in typologies, spotting anomalies and understanding chargeback and dispute cycles. Velocity Features, Device Dynamics and Entity Profiling. Financial and Regulatory Guardrails.
- Excellent English language skills, and preferable German language skills.
- Very strong communication skills, to both technical and non technical members and ability to explain complex statistical outputs to non technical officers.
- Ability to grasp new business concepts and translate them into technical requirements.
- Crisis communication under pressure in periods of unplanned situations.
- Adaptability and continuous learning.
- Adversarial & Skeptical mindset.
- Ability to mentor and inspire team members.
- Comfortable working with AI tools, thinking critically about AI outputs, and contributing to a culture of responsible AI use. We expect you to demonstrate comfort with AI-assisted workflows and a willingness to continuously develop their AI capabilities as the technology evolves.
Erfahrung
- Minimum 6 years experience in a role of data scientist in a fast pace environment and regulated industry.
- Advanced SQL skills (window functions, query optimisation) and hands on experience in analytical platforms (ideally Snowflake by utilising snowpark).
- Experience working with centralized feature platforms (e.g., Snowflake Feature Store, Feast, Tecton) to prevent train-serve skew.
Unser Angebot
- Home office budget.
- Learning & development budget of €1000 per year and a transparent growth framework to support your career goals.
- Competitive salary and a variable remuneration program.
- Monthly meal allowance.
- Deutschland ticket subsidy.
- 28 vacation days, increasing by 2 days after 2 years and 3 days after 3 years with Solaris.
- Opportunity to work abroad for up to 12 weeks per year.
Benefits
Work-Life-Integration
Themen mit denen du dich im Job beschäftigst
Job Standorte
Das ist dein Arbeitgeber
SolarisBank
Wir nutzen die Möglichkeiten von Banking-as-a-Service, um die Hürden für Unternehmen zu beseitigen, die eigene Finanzprodukte anbieten wollen. Unsere proprietäre Banking-as-a-Service-Plattform ermöglicht es jedem Unternehmen, Finanzdienstleistungen in neue Kontexte zu integrieren, die vorher unvorstellbar waren.
Description
- Unternehmenstyp
- Etablierte Firma
- Arbeitsmodell
- Hybrid, Onsite
- Branche
- Banken, Finanz, Versicherung
Senior Data Scientist
- Gehalt
- 80.000 bis 100.000€ Brutto/JahrNetto aus dem Bruttogehalt im Inserat mit Steuerklasse I umgerechnet.48.049 bis 58.031 € netto/Jahr · Steuerklasse I
- Ort
- Berlin
- Arbeitsmodell
- Hybrid, Onsite
- Diversität
- Für alle Personen geeignet (m/w/d)
