AVP, Data Science - AI Graph Expert (29839)
- Help the AI CoE team to build and scale analytics solutions leveraging graph-based machine learning/deep learning capabilities
- Support the business teams to identify patterns and relationships between complex entities and concepts through the use machine learning on graph databases/knowledge graphs
This is a hands-on position where you will be empowered to be creative, ambitious, and bold; to solve novel problems and have the potential to directly impact the lives of people around the world. We have impressive toolkits and clients with world class data, and we are now looking for talented people to join our team.
- Must be legally authorized to work in the United States without the need for employer sponsorship, now or at any time in the future
- A degree in Engineering, Statistics, Data Science, Applied Mathematics, Computer Science, Physics, Computational Biology, Computational Chemistry or related quantitative field (Masters or PhD preferred for Senior Manager direct hires)
- Experience in creating and maintaining graph data models.
- Expertise in machine learning/deep learning-based graph algorithms relevant to link prediction, ranking/recommendation, completion, community detection, node embedding, etc.
- Expert understanding of a programming language such as Python.
- Experience with at least one Deep Learning framework such as PyTorch or TensorFlow/Keras
- Demonstrated ability to write high-quality, production-ready code (readable, well-tested, with well-designed APIs) m ethods that go beyond putting together of existing code, and to apply problem-solving skills to complex issues
- Excellent written and verbal communication skills
- Ability to work autonomously and collaboratively as part of a team to both teach and learn every day
- Continuously looking for opportunities to learn, build skills and share learning.
- PhD or Master's degree
- A domain specialization such as Cyber Security, Fraud/Waste/Abuse, or Data Management
- Proficiency in Linux environment (including shell scripting), experience with database languages (e.g., SQL, No-SQL) and experience with version control practices and tools (Git, Perforce, etc.)
- Familiarity with cloud computing services (AWS, GCP, or Azure)
- Experience with large-scale deep learning model training