NEXGEN Asset Management · 17 hours ago
Data Scientist (Data Warehouse Experience)
NEXGEN Asset Management is a leading Enterprise Asset Management platform specializing in data-driven decision-making. They are seeking a detail-oriented Data Scientist with Data Warehouse experience to design and optimize their data infrastructure, develop data science solutions, and collaborate with data and product teams.
Software
Responsibilities
Data Warehouse Design: Design, build, and maintain the company’s data warehouse to support scalable analytics and reporting
Data Modeling: Create and evolve star schemas and warehouse structures optimized for analytics and reporting
ETL / ELT Pipelines: Develop and maintain pipelines that integrate data from application and operational systems
Data Quality & Governance: Ensure accuracy, consistency, documentation, and reliability of warehouse data
Performance Optimization: Monitor and optimize query performance and warehouse efficiency
AI Readiness: Support AI and advanced analytics initiatives by ensuring high-quality, ML-ready data
Collaboration: Work with product and analytics teams to translate requirements into data solutions
Modeling: Develop, train, and evaluate machine learning models (e.g., decision trees, regression, and classification models)
Qualification
Required
Candidates must be authorized to work in the U.S. without sponsorship now or in the future
Master's degree in Data Science, Computer Science, Artificial Intelligence, or a related quantitative field
Developing, deploying, and maintaining machine learning models in production environments
Designing, building, and maintaining a data warehouse
Strong background in statistical analysis, data preparation, and databases
Proficiency in Python, ML libraries (Scikit-learn, TensorFlow, PyTorch), and SQL
Strong analytical and problem-solving mindset
Effective collaboration with technical and non-technical teams
Clear communication of complex concepts
Preferred
Experience supporting AI or machine learning workflows
Experience using Postgres
Experience in a small company or high-ownership environment