The Financial Services team is looking for talented Network Data Scientists to help execute this vision. You’ll work closely with our Clients, Data Scientists, Product Managers, Software Engineers, and leadership team to develop analytics that provide insights on network dynamics and their impacts on financial performance in supplier networks.

Responsibilities

• Develop statistical models of network structures and their relationships to network behavior
• Automate identification of persistent network structures as well as emergent network structures and behaviors
• Build analytical solutions for understanding network dependencies
• Establish metrics for common network attributes such as attachment, centrality, connectivity, distance, path lengths, and similarity
• Develop new metrics that describe network characteristics as relates to the performance of businesses in the network 
• Develop models to describe, predict, and simulate network behavior under multiple scenarios 
• Categorize relationships between network patterns and business outcomes
• Build descriptive and predictive models of network dynamics that can be used to plan business strategies by people regardless of their expertise in network analytics

About You

• BS, MS, or PhD degree in Computer Science, Data Science, Economics, Statistics, Computational Biology, BioInformatics, or equivalent experience
• You have a strong background in data science, graph mining, and graph simulations
• You enjoy sharing your expertise using Python for graph analysis and machine learning
• You have experience with data intensive applications and complex systems
• You are energized by power laws, long-tail effects, and nonlinear system dynamics 
• You are comfortable communicating technical analysis to less technical stakeholders
• You are interested in applying network analysis to improve the world
• You have strong written and verbal communication skills

Nice to have, but not required

• Experience with Apache Spark, Databricks
• Experience with generative models of network structure and behavior
• Experience analyzing supplier networks in supply chains, banking, insurance, or ecommerce

Technologies we love

• Languages: Python, Spark, SQL
• Tools: Scikit-learn, Numpy, Pandas, NetworkX, PyTorch, Tensorflow, DGL
• Datastores: Databricks, Elasticsearch, Postgres, RDS, Kafka