AI and Data Scientist - Geospatial

19h19 hours ago

MSCI

Budapest, HU · Full-time

About this role

We are developing cutting-edge tools to identify and analyze climate change risk exposure of companies and real estate investments. Our models simulate natural and physical risks into insightful metrics for investors. A cornerstone of our climate modeling capabilities is our GeoSpatial dataset of asset locations.

The team is seeking an AI and Data Scientist to contribute to the development of novel data extraction tools and workflows. You will design, prototype, and evaluate scalable models including LLMs to improve asset detection and attribute inference. Additionally, you will experiment with state-of-the-art ML techniques like RAG pipelines, computer vision, and geospatial ML.

Work with engineers to deploy systems into production. You will co-lead R&D projects exploring novel methods for extracting information from diverse data sources. This role requires deep expertise in AI and ML approaches to data collection and evaluation.

MSCI offers transparent compensation schemes and comprehensive employee benefits tailored to your location. Flexible working arrangements and a culture of high performance and innovation foster growth. A global network of talented colleagues and multi-directional career paths support your professional development.

Requirements

Strong background in Machine Learning and AI, including hands-on experience with LLMs, transformers, embeddings, and deep learning frameworks (PyTorch, TensorFlow, JAX).
Expertise in Python and common data-science libraries (Pandas, NumPy, Scikit-learn).
Experience building data-extraction pipelines using NLP, vision models, information retrieval, or weak supervision.
Experience with geospatial data using tools such as GeoPandas, GDAL, Rasterio, Shapely, or PostGIS is desirable.
Hands-on experience in cloud environments (GCP, AWS, or Azure) and cloud-native geospatial workflows are desirable.
Strong understanding of data quality workflows, anomaly detection, and validation frameworks.
PhD/MSc degree in Computer Science, Data Science, Machine Learning, Geospatial Science, Environmental Science, or a related field; or equivalent hands-on experience.

Responsibilities

Contribute to and co-lead R&D projects exploring novel methods for extracting information from structured, semi-structured, and unstructured data (documents, imagery, text, APIs, geospatial data sources).
Design, prototype, and evaluate scalable models, including LLMs, to improve asset detection, attribute inference, and classification with robust QA and data-validation processes.
Experiment with state-of-the-art ML techniques (LLMs, RAG pipelines, computer vision, geospatial ML, anomaly detection, weak supervision, multimodal models).
Work with engineers to deploy systems into production.
Develop novel data extraction tools and workflows to expand coverage of physical and natural assets and their associated attributes.
Further our QA processes for data quality and validation.

Benefits

Transparent compensation schemes and comprehensive employee benefits tailored to your location.
Flexible working arrangements, advanced technology, and collaborative workspaces.
A culture of high performance and innovation where we experiment with new ideas.
A global network of talented colleagues who inspire and share expertise.
Global Orientation program and access to Learning@MSCI platform, LinkedIn Learning Pro, and tailored learning opportunities.
Multi-directional career paths offering professional growth through new challenges, internal mobility, and expanded roles.