Themis
Data Scientist / ML Engineer
Vaga remota de Data Science com fit claro de localização do candidato.
Publicada1 de jul. de 2026
Países elegíveis1 país aceito
Sinal de senioridadeSenior
Modelo de trabalhoRemoto
Locais aceitos para candidatos
Estados Unidos
Resumo da vaga
Data Scientist / ML Engineer
Requisitos e responsabilidades
Conteúdo da vaga extraído em seções para revisão mais rápida.
Modeling & Experimentation
- Frame ambiguous compliance and risk problems as well-defined data and modeling tasks
- Build, evaluate, and iterate on machine learning models and LLM-powered features
- Design experiments and define metrics that measure real impact on customer workflows
- Apply rigorous evaluation, including accuracy, explainability, and bias considerations appropriate to a regulated domain
Production ML & Engineering
- Build and maintain data and ML pipelines for training, inference, and monitoring
- Deploy models and AI features into production and monitor their performance over time
- Collaborate with engineering to integrate models into the Themis platform reliably and at scale
- Implement guardrails, evaluation harnesses, and monitoring for AI-powered features
Data & Insight
- Explore and prepare data, build features, and ensure data quality and integrity
- Translate data and model findings into clear recommendations for product and leadership
- Partner with Product to identify high-value opportunities for ML and AI
Required Qualifications
- Strong foundation in machine learning, statistics, and data science fundamentals
- Proficiency in Python and common data and ML libraries (e.g., pandas, scikit-learn, PyTorch, or TensorFlow)
- Experience taking models or data products from prototype to production
- Experience with SQL and working with real-world, messy data
- Ability to design experiments, define metrics, and evaluate models rigorously
- Strong communication skills and the ability to explain technical work to non-technical stakeholders
- Ability to manage ambiguity and own problems end to end
Preferred Qualifications
- Experience building with large language models, retrieval-augmented generation, or modern AI tooling
- Experience deploying and monitoring ML in production (MLOps)
- Experience in financial services, compliance, risk, fraud, or other regulated or high-stakes domains
- Familiarity with cloud data and ML platforms (e.g., AWS, GCP, or Azure)
- Experience working in a startup or high-growth company
Vagas similares
Mantenha uma lista reserva.
Stack
Use estas tags para comparar vagas remotas similares.
Elegibilidade de localização
Candidatos devem aplicar apenas quando o país do perfil estiver listado aqui.
Seu perfilPaís não definidoEntre para comparar seu país com esta vaga.
Fluxo de contratação
O WithMira mostra a vaga e depois envia candidatos para a aplicação da empresa.
1Confira fit da vaga, stack e elegibilidade de localização no WithMira.
2Abra a página de aplicação da empresa pelo link rastreado.
3Salve a vaga ou assine oportunidades similares antes de sair.