Senior Data Scientist
Clera · Data · Senior · 10d ago
Open to candidates across EU.
Applies on the original listing · via Himalayas
Who can apply
Read straight from the listing, so you know before you spend time on it.
Open to candidates across EU.
“Fully remote within the EU.”
- Async-first
- The listing doesn't promise async-first working.
- Contractor / B2B
- No mention of hiring international contractors or invoicing.
- Global stipend
- No home office or equipment budget mentioned.
- Annual retreat
- No company-paid get-togethers mentioned.
Read from the listing automatically. Always confirm the details with the company before you accept an offer.
About the role
In this hybrid data science and ML infrastructure role, you will build production-grade models and establish the evaluation, deployment, and monitoring foundations that ensure ML systems remain reliable as they scale. You will work across transaction coding suggestions, document understanding, and retrieval-augmented systems while shaping engineering standards for the team.
What you'll do
- Define and evolve practices for evaluating, deploying, monitoring, versioning, and retraining models.
- Design evaluation frameworks and test harnesses to assess model quality before and after launch.
- Build and own models and analyses for transaction coding suggestions, document understanding, and retrieval-augmented or agentic systems.
- Partner with data engineering on infrastructure decisions such as model registries, feature stores, serving patterns, and monitoring drift.
- Translate ambiguous business needs into modeling questions and design experiments to measure impact.
What you bring
- At least 6 years of data science or applied ML experience, including models shipped to production.
- Strong knowledge of ML infrastructure such as deployment, monitoring, retraining, model registries, feature stores, and evaluation frameworks.
- Proficiency in Python, SQL, statistical modeling, and experiment design.
- Experience establishing ML or data science practices and technical standards on a team.
- Familiarity with relevant tools such as Snowflake, dbt, PostgreSQL, Kubernetes, MLflow, Terraform, or Google Cloud services.
About Clera
Clera is a fintech company that develops intelligent data products and automated solutions for financial data.
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