We are seeking a Principal Data Scientist with strongly developed expertise in graph-based AI and related technologies to maximize utilization of data and knowledge in the client's data and digital transformation.
Degree in mathematics, computer science, engineering, physics, statistics, economics, computational sciences or a related quantitative discipline and 5+ years of analytical experience in an industrial or commercial setting OR PhD degree with at least 3+ years of industry experience
Experience AI/ML/NLP modelling of complex datasets.
Advanced software development skills in at least two of the standard data science languages (such as Python, R, Scala, C++, Julia) and strong data manipulations skills (e.g. SQL, NoSQL, graph, etc.)
Knowledge of SQL and relational databases, query authoring (SQL) and designing variety of databases (e.g. Postgres SQL)
Comfortable working in cloud and high-performance compute environments (e.g. AWS, Apache Spark)
Disciplined AI/ML deployment (MLOps, CI/CD) and Agile delivery
Experience in coordination of delivery teams and providing feedback to their management
Excellent written and verbal communication, business analysis, and consultancy skills
Knowledge on health care knowledge management systems (e.g. ICD, SNOMED, MedDRA, UMLS) preferred
Experience AI/ML modelling of complex datasets, network analysis or direct experience in creating and maintaining graph data models
Experience with a variety of graph technologies Knowledge of graph databases like Neo4J (Cypher, causal clusters), JanusGraph (Gremlin, GraphML), AWS Neptune, OrientDB
Expertise in machine learning/deep learning-based graph algorithms relevant to link prediction, ranking/recommendation, completion, community detection, node embedding, etc.
Lead data science area deliverables for digital products / programs / initiatives including the allocation of work within the team, monitors the quantitative and qualitative achievements of the team, and reports results
Work as an individual contributor, providing data science expertise to digital products / programs / initiatives.
Apply in-depth experience with both statistical and modern data science approaches, including unsupervised, supervised, regression algorithms.
Apply advanced techniques such as neural networks, deep learning, NLP and federated learning.
Build models, algorithms, simulations and experiments by writing highly optimized code and using state-of-the art machine learning technologies.
Collaborate cross-functionally in teams involved in data driven analytics to maximize impact of graph-based capabilities
Build and manage support models incorporated into digital or AI products; Work with Infrastructure and Ops teams to ensure appropriate architecture and tooling
Capacity to mentor junior personnel
Be able to apply in-depth experience with both statistical and modern data science approaches to business cases and knowledge management tasks
Strong written and verbal communication skills - ability to communicate complex ideas up to people of varying technical skills
Work with developers, engineers, and MLOps to deliver AI/ML solutions for new products/services