Job
- Level
- Senior
- Job Field
- Data
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Salary
- 80.000 to 100.000€ gross/year
- Location
- Berlin
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you develop Machine Learning models for fraud protection and compliance, prepare training data, conduct feature engineering, and optimize models while closely collaborating with stakeholders and the infrastructure team.
Job Technologies
Your role in the team
- Development, operationalization, and maintenance of Machine Learning models in close collaboration with business stakeholders for common risk and financial protection with varying 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.
- Kontinuierliches Lernen durch die Einrichtung automatisierter Pipelines, die Bevölkerungsverschiebungen überwachen und Modelle bei neuen Daten kontinuierlich neu anpassen, wenn die Leistung unter vordefinierte betriebliche Benchmarks fällt.
- Knowledge sharing and mentoring across the team.
This text has been machine translated. Show original
Our expectations of you
Education
- Degree in Computer Science, Applied Mathematics, Statistics, Quantitative Finance, and targeted Financial Engineering courses.
Qualifications
- Proficiency in data science libraries (pandas, polars, numpy, scikit-learn) and gradient boosting frameworks (XGBoost).
- Gute Kenntnisse in Data-Transformation- und Data-Orchestration-Tools, idealerweise dbt und 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.
- Krisenkommunikation unter Druck in Zeiten unvorhergesehener Situationen.
- 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.
Experience
- 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.
This text has been machine translated. Show original
What we offer
- Home office budget.
- Learning & development budget of €1000 per year and a transparent growth framework to support your career goals.
- Wettbewerbsfähiges Gehalt und ein variabler Vergütungsplan.
- Monatliche Essenszulage.
- Germany 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.
This text has been machine translated. Show original
Benefits
Work-Life-Integration
Topics You Will Work On
Job Locations
About Your Employer
SolarisBank
We are leveraging the power of Banking-as-a-Service to remove the barriers for companies to offer their own financial products. Our proprietary Banking-as-a-Service platform enables any business to integrate financial services into new contexts that were previously unimaginable.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Banking, Finance, Insurance
Senior Data Scientist
- Salary
- 80.000 to 100.000€ gross/yearEstimated net salary based on the gross salary in the job ad using tax class I.48.049 to 58.031 € net/year · Tax class I
- Location
- Berlin
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
