Role overview
Data Scientist (Machine Learning & AI Systems)
The Data Scientist will be responsible for the end-to-end design, implementation, deployment, and maintenance of data-driven and AI-powered software systems supporting MAYA PCI’s private debt and real-estate investment activities.
Key responsibilities include:
- Develop Large Language Model (LLM)-based systems for advanced document analysis, knowledge extraction, and decision support.
- Design and deploy Retrieval-Augmented Generation (RAG) pipelines integrating semantic retrieval, vector databases, and generative models.
- Fine-tune and adapt large language models for domain-specific use cases in finance, legal documentation, and private debt.
- Build and maintain end-to-end data pipelines, covering data ingestion, preprocessing, feature engineering, model training, inference, and evaluation.
- Design, develop, and maintain production-grade software applications, including backend services, APIs, and internal tools.
- Develop user-facing applications and dashboards, enabling business users to interact with AI and data systems.
- Deploy and operate AI and data systems on Microsoft Azure, including cloud services, AI platforms, and automation workflows.
- Ensure scalability, security, and reliability of deployed systems in a regulated financial environment.
Technical Qualifications
- Master’s degree (or final-year student) in Computer Science, Data Science, Machine Intelligence, or a related technical field.
- Degree from ETH Zurich, EPFL, or an equivalent top-tier technical university.
- 1–2 years of relevant experience through technical internships, part-time roles, or applied research projects.
- Frontend development: HTML, CSS, JavaScript, Vue.js or React, Dash, Streamlit
- Backend development: Python, FastAPI or Flask, REST APIs, integration of machine learning and LLM models into backend services
- Machine learning & deep learning: PyTorch, scikit-learn, NumPy, Pandas, SciPy, model training, evaluation, and optimization
- Hands-on experience with Large Language Models, including:
- LangChain-based applications
- Retrieval-Augmented Generation (RAG)
- Embeddings and vector similarity search
- Databases & data architecture: SQL, relational database design, schema optimization, integration with applications and AI pipelines
- Cloud & production systems: Linux environments, Docker, cloud deployment on Microsoft Azure, Azure AI services
- DevOps & reliability: CI/CD pipelines, automation, basic monitoring, production system maintenance
- Solid understanding of financial data and private debt instruments.
- Ability to work independently in small, technically demanding teams.
- Fluent English (mandatory).
- Fluent French (mandatory).
Preferred Qualifications
- Research-oriented project, thesis, or publication involving LLMs, NLP, or advanced ML systems.
- Experience with model fine-tuning and domain adaptation.
- Experience with Azure AI Studio, MLOps, or production model serving.
- Ability to build end-to-end applications, including backend services and user-facing interfaces
- Experience modeling financial workflows such as interest accrual, repayment schedules, and servicing events.
About MAYA PCI
MAYA PCI is a Geneva-based investment firm specializing in private debt and real-estate financing. The firm develops proprietary data and AI platforms to support investment analysis, loan servicing, and portfolio monitoring.
Operating in a highly regulated and data-intensive environment, MAYA PCI relies on advanced data science, machine learning, and cloud-based systems to maintain its competitive advantage.
Job Type: 100%
Pay: CHF70’000.00 - CHF110’000.00 per year
Work Location: In person
What you'll work on
The Data Scientist will be responsible for the end-to-end design, implementation, deployment, and maintenance of data-driven and AI-powered software systems supporting MAYA PCI’s private debt and real-estate investment activities.
- Develop Large Language Model (LLM)-based systems for advanced document analysis, knowledge extraction, and decision support.
- Design and deploy Retrieval-Augmented Generation (RAG) pipelines integrating semantic retrieval, vector databases, and generative models.
- Fine-tune and adapt large language models for domain-specific use cases in finance, legal documentation, and private debt.
- Build and maintain end-to-end data pipelines, covering data ingestion, preprocessing, feature engineering, model training, inference, and evaluation.
- Design, develop, and maintain production-grade software applications, including backend services, APIs, and internal tools.
- Develop user-facing applications and dashboards, enabling business users to interact with AI and data systems.
- Deploy and operate AI and data systems on Microsoft Azure, including cloud services, AI platforms, and automation workflows.
- Ensure scalability, security, and reliability of deployed systems in a regulated financial environment.
What we're looking for
- Master’s degree (or final-year student) in Computer Science, Data Science, Machine Intelligence, or a related technical field.
- Degree from ETH Zurich, EPFL, or an equivalent top-tier technical university.
- 1–2 years of relevant experience through technical internships, part-time roles, or applied research projects.
- Frontend development: HTML, CSS, JavaScript, Vue.js or React, Dash, Streamlit
- Backend development: Python, FastAPI or Flask, REST APIs, integration of machine learning and LLM models into backend services
- Machine learning & deep learning: PyTorch, scikit-learn, NumPy, Pandas, SciPy, model training, evaluation, and optimization
- Hands-on experience with Large Language Models, including:
- LangChain-based applications
- Retrieval-Augmented Generation (RAG)
- Embeddings and vector similarity search
- Databases & data architecture: SQL, relational database design, schema optimization, integration with applications and AI pipelines
- Cloud & production systems: Linux environments, Docker, cloud deployment on Microsoft Azure, Azure AI services
- DevOps & reliability: CI/CD pipelines, automation, basic monitoring, production system maintenance
- Solid understanding of financial data and private debt instruments.
- Ability to work independently in small, technically demanding teams.
- Fluent English (mandatory).
- Fluent French (mandatory).
- Research-oriented project, thesis, or publication involving LLMs, NLP, or advanced ML systems.
- Experience with model fine-tuning and domain adaptation.
- Experience with Azure AI Studio, MLOps, or production model serving.
- Ability to build end-to-end applications, including backend services and user-facing interfaces
- Experience modeling financial workflows such as interest accrual, repayment schedules, and servicing events.
About MAYA PCI
MAYA PCI is a Geneva-based investment firm specializing in private debt and real-estate financing. The firm develops proprietary data and AI platforms to support investment analysis, loan servicing, and portfolio monitoring.
Operating in a highly regulated and data-intensive environment, MAYA PCI relies on advanced data science, machine learning, and cloud-based systems to maintain its competitive advantage.
Job Type: 100%
Pay: CHF70’000.00 - CHF110’000.00 per year
Work Location: In person