Senior Graph Data Scientist – Identity Analytics

Senior Graph Data Scientist – Identity Analytics responsible for developing and implementing quantitative solutions to detect and prevent identity theft, account takeover, and first party/synthetic fraud. The role requires strong experience in machine learning, graph analytics, and data analysis. Emphasis is placed on developing scalable, automated solutions using machine learning, simulation, and optimization to deliver business insights and business value.

Requirements

• 6 years of experience in predictive analytics or data analysis
• 4 years of experience in training and validating statistical, physical, machine learning, and other advanced analytics models
• 4 years of experience in one or more dynamic scripted language (such as Python, R, etc.) for performing statistical analyses and/or building and scoring AI/ML models
• Strong experience in querying and preprocessing data from structured and/or unstructured databases using query languages such as SQL, NoSQL, etc.
• Strong experience in working with structured, semi-structured, and unstructured data files such as delimited numeric data files, JSON/XML files, and/or text documents, images, etc.
• Demonstrated skill in performing ad-hoc analytics using descriptive, diagnostic, and inferential statistics
• Ability to assess and articulate regulatory implications and expectations of distinct modeling efforts
• Advanced experience with the concepts and technologies associated with classical supervised modeling for prediction such as linear/logistic regression, discriminant analysis, support vector machines, decision trees, and ensemble methods such as Random Forests, XGBoost, LightGBM, and CatBoost
• Advanced experience with the concepts and technologies associated with unsupervised modeling such as k-means clustering, hierarchical/agglomerative clustering, neighbors algorithms, DBSCAN, etc.
• Experience guiding and mentoring junior technical staff in business interactions and model building
• Experience communicating analytical and modeling results to non-technical business partners with emphasis on business recommendations and actionable applications of results

Benefits

• Comprehensive medical, dental and vision plans
• 401(k)
• Pension
• Life insurance
• Parental benefits
• Adoption assistance
• Paid time off program with paid holidays plus 16 paid volunteer hours
• Various wellness programs
• Career path planning and continuing education