As a Data Scientist at Datonomy Solutions, you'll leverage your expertise in graph analytics and machine learning to drive innovative solutions. This role is ideal for someone who enjoys working with complex data structures and has a strong background in Python.
At Datonomy Solutions, the Data Scientist role is centered around utilizing TigerGraph and graph analytics to develop advanced machine learning solutions. You will be responsible for designing and operationalizing graph-based models that enhance decision-making and risk assessment processes. Your work will involve creating reusable features from graph data that can be integrated into various systems.
In this position, you will engage with cloud-native infrastructure, specifically using AKS Kubernetes for deployment and management. You will also focus on data ingestion and performance optimization to ensure that the systems you develop are resilient and efficient. Your strong Python skills will be crucial for automating processes and conducting graph analytics.
This role is well-suited for experienced data scientists who have a passion for graph machine learning and a solid understanding of knowledge graphs. You should be comfortable working with complex data relationships and have a proactive approach to problem-solving. Key requirements include a strong background in graph-derived feature engineering and familiarity with graph neural networks.
Overall, this position offers a unique opportunity to work at the intersection of data science and advanced graph technologies, making a significant impact on the company's analytics capabilities.
You'll be taken to the original listing on PNet to apply.