or apply directly on Solaris's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 8 days Solaris's roles stay open a median of 45 days
- Reposted
- No
- Salary listed
- No 0% of Solaris's roles list one
- Ghost-job risk at Solaris
- high 19 stale, 4 reposted of 27 open
- Hiring momentum
- 46 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-09-17
Measured from postings appearing on and disappearing from Solaris's own greenhouse board since 2026-08-03. Full hiring picture for Solaris.
About this role
As a Senior Data Scientist at Solaris, you will develop, operationalize, and maintain Machine Learning models focused on risk and financial protection, collaborating closely with business stakeholders. Your role includes preparing training data, performing feature engineering, selecting and training models, and deploying them while ensuring continuous learning through automated monitoring pipelines. You will also share knowledge and mentor team members, contributing to the transition into an AI-native banking platform.
- benefits
- 4/5
- freshness
- 5/5
- career value
- 4/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of Solaris as an employer.
What you need
- Degree in Computer Science, Applied Mathematics, Statistics, Quantitative Finance, or targeted Financial Engineering courses
- Minimum 6 years experience as a data scientist in a fast-paced 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 optimization) and hands-on experience in analytical platforms (ideally Snowflake by utilizing snowpark)
- Experience with centralized feature platforms (e.g., Snowflake Feature Store, Feast, Tecton)
- Good knowledge of data transformation and orchestration tools, ideally dbt and airflow
What you get
- Home office budget
- Learning & development budget of €1000 per year
- 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
Worth weighing
- No specific mention of remote work flexibility beyond home office budget
- Salary range provided, but no details on how performance impacts compensation
- Emphasis on adaptability and continuous learning may indicate a fast-evolving work environment
Summarised from Solaris's posting. Read the full original.
Listed by Solaris on their greenhouse job board, last confirmed open on 2026-09-17. PitchMeAI is not the employer.
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