May (And ideally start the week commencing the 26th of May) Desirable Skills/Experience: 1. GIS experience and proficiency with geospatial libraries (e.g., GeoPandas, QGIS, PostGIS). 2. Familiarity with Databricks and distributed computing frameworks (e.g. Spark). 3. Exposure to CI/CD pipelines and workflow automation. 4. More ❯
for time series, spatial, and network data. Excellent programming skills in common languages (e.g., Python) and packages used by the energy modeling field (e.g., geopandas, numpy, networkx, pandas), use of software best practices (e.g., Git), and familiarity with high-performance computing environments. Experience with extracting, transforming, and loading processes and More ❯
enable the transformation and analysis of large-scale geospatial datasets. Skills and Experience: Strong programming skills in Python, with experience using libraries such as GeoPandas, Shapely and GDAL Experience with cloud platforms (AWS, Azure or GCP) and infrastructure-as-code tools Proficiency in spatial databases (e.g., PostGIS) and data pipeline More ❯
Skills & Experience: 5+ years of relevant industry experience, ideally within financial services, capital markets, or asset management sectors. Proficient in Python 3, including pandas, GeoPandas, boto3, Pydantic, and Data Version Control (DVC). Familiar with Django 4 and core API development. Strong hands-on experience with AWS cloud infrastructure, EKS More ❯
science, or software engineering roles • Bachelor’s degree or equivalent in Computer Science, Data Science, or related technical field • Strong Python programming (especially pandas, GeoPandas, Pydantic, boto3) • Experience with geospatial data and data engineering for ML applications • Cloud proficiency (preferably AWS) and experience with containerized environments (Docker, EKS) • Solid Git … to collaborate with cross-functional teams • Experience working with financial services or asset management domains preferred Technical Stack: Data Pipeline Stack: Python 3, pandas, GeoPandas, boto3, Pydantic, Data Version Control (DVC) 2 Core API Stack: Python 3, Django 4 Infrastructure: AWS, EKS, Docker, ADO (for CI/CD pipelines, git More ❯
science, or software engineering roles • Bachelor’s degree or equivalent in Computer Science, Data Science, or related technical field • Strong Python programming (especially pandas, GeoPandas, Pydantic, boto3) • Experience with geospatial data and data engineering for ML applications • Cloud proficiency (preferably AWS) and experience with containerized environments (Docker, EKS) • Solid Git … to collaborate with cross-functional teams • Experience working with financial services or asset management domains preferred Technical Stack: Data Pipeline Stack: Python 3, pandas, GeoPandas, boto3, Pydantic, Data Version Control (DVC) 2 Core API Stack: Python 3, Django 4 Infrastructure: AWS, EKS, Docker, ADO (for CI/CD pipelines, git More ❯
