Data Scientist at ParallelScore
Job Description
We are seeking an experienced Data Scientist with strong expertise in graph analytics and Neo4j to build intelligent models that uncover hidden relationships and optimise decision-making. You will design and implement analytical frameworks using graph data, AI, and statistical modelling.
Must Have Capability
- Design and execute graph-based analytical models using Neo4j, Cypher, and the Graph Data Science Library.
- Develop machine learning and predictive models leveraging graph embeddings.
- Collaborate with data engineers to prepare and transform large, complex graph datasets.
- Apply algorithms such as community detection, link prediction, and centrality analysis.
- Communicate findings through data visualisation and storytelling to business stakeholders.
Required Skills & Experience
- 5+ years of experience in data science or analytics.
- Proficiency with Neo4j, Cypher, and graph-based data modelling.
- Strong programming skills in Python (pandas, scikit-learn, PyTorch/TensorFlow).
- Solid foundation in statistics, feature engineering, and ML pipelines.
- Familiarity with cloud platforms and Databricks for data preparation.
Preferred
- AWS Cloud certification
- Knowledge of graph neural networks (GNNs) or advanced graph embeddings.
- Experience deploying models into production (APIs, dashboards).
