Senior Data Scientist

DUDE CHEM; Berlin; Hybrid; EUR 80.000 - 100.000; Vollzeit

Benefits dieser Stelle

Home office budget

Learning budget €1000/yr

Competitive salary with bonus

Monthly meal allowance

Deutschland ticket subsidy

28 vacation days (+2/3 after years)

Opportunity to work abroad up to 12 w/

Zusammenfassung

Solaris is seeking a senior data scientist to design, train and deploy ML models for fraud, compliance and risk. You will work with large transactional data, engineer features, manage a central feature store, and collaborate with analytics engineers to productionize solutions.

The role emphasizes scalable ML, data governance, and clear communication across technical and non-technical stakeholders within a Berlin-based team.

Qualifikationen

• Minimum 6 years experience as a data scientist in fast paced, regulated environments.
• Proficiency with Python libraries for data science and ML model development.
• Strong SQL skills including window functions and performance tuning.
• Experience with centralized feature platforms and data orchestration tools.
• Familiarity with CI/CD, Git and automated testing practices.
• Excellent English; German language skills are a plus.

Aufgaben

• Develop, operationalise and maintain ML models in collaboration with stakeholders.
• Prepare training data from large transactional logs and label data as needed.
• Engineer features and manage a central feature store for reliable serving.
• Experiment, train and evaluate models with clear trade-offs and metrics.
• Deploy models and support batch and online prediction with data infra team.
• Set up pipelines to monitor drift and re-train models as needed.
• Share knowledge and mentor colleagues across the team.

Kenntnisse

Machine Learning

Python

SQL

Data Analysis

Feature Store

Snowflake

Snowpark

Feast

Tecton

Git & CI/CD

Ausbildung

Degree in CS/Math/Stats/Finance

Tools

Snowflake Feature Store

Feast

Tecton

Snowpark

Jobbeschreibung

Solaris is Europe’s leading embedded finance platform, pioneering Banking-as-a-Service to bridge the gap between financial technology and licensed banking. Founded in 2016 and headquartered in Berlin, Solaris enables fintechs, digital ecosystems, and multinationals to embed accounts, cards, lending, and payments directly into their own products, creating seamless financial experiences for their users. As a fully licensed German bank, Solaris combines the highest standards of IT security and regulatory resilience with a modular, highly scalable infrastructure.

Today, Solaris is driving the next evolution of financial services by transitioning into an AI-native banking platform, ensuring European businesses can deploy secure, adaptable financial products at scale.

Why join Solaris?

• We are fundamentally redesigning banking processes around AI orchestration, standardized modular building blocks, and embedded regulatory compliance.
• We combine tech and banking in dedicated hubs – driving the technology infrastructure out of Berlin and banking operations out of Frankfurt.
• Through our internal mobility, growth opportunities, and the Solaris Academy, we offer continuous learning tracks, AI ambassador mentorship, and upskilling to keep your skills ahead of the curve.
• We foster a workplace rooted in integrity, proactive risk management, and equality actively driving initiatives like DEI initiatives.

Your Role

• 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.

We'd love to see

Depending on your level of experience, your responsibilities and scope of role will range. We don’t care much about fancy titles, but rather about real personal and professional development, as laid out in ourlearning framework. Let’s figure together out how you can contribute to our team.

• Degree in Computer Science, Applied Mathematics, Statistics, Quantitive Finance and targeted Financial Engineering courses.
• Minimum 6 years experience in a role of data scientist in a fast pace environment and regulated industry.
• Proficiency in data science libraries (pandas, polars, numpy, scikit-learn) and gradient boosting frameworks (XGBoost).
• 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.
• 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.

Benefits

• 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 towork abroad for up to 12 weeks per year.

At Solaris, we are committed to nurturing an inclusive environment, where all Solarians feel valued, respected and supported. We are dedicated to building a diverse workforce that reflects the diversity of our communities. We are committed to equal employment opportunity regardless of color, ethnicity, religion, sex, origin, disability, marital status, citizenship, or gender identity. We are proud to be an equal opportunity workplace. If you have a disability or special need that requires accommodation, please let us know.

If your application is successful, you will be required to complete pre-employment background checks through our screening provider Zinc. These include, but not limited to identity verification, educational records, references, a criminal record check, etc. The processing is based on Art. 6(1)(c) GDPR. Please see below Privacy Information for Job Applicants for details, including recipients, retention, and your rights.

Information on data processing:

DE: https://www.solarisgroup.com/gdpr_notice_de
EN: https://www.solarisgroup.com/gdpr_notice_en

The annual gross salary range for this position is:€80.000—€100.000 EUR