Data Scientist at ParallelScore

• We are seeking an experienced Data Scientist with strong expertise in graph analytics and Neo4j to build intelligent models that uncover hidden relationships and optimize decision-making. You will design and implement analytical frameworks using graph data, AI, and statistical modeling.

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 visualization 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 modeling.
• 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).