Our behavioral analytics team supports a wide variety of federal agency client needs focused on detecting fraudulent electronic transactions/usage. Team members will work collaboratively with the Noblis data analytics architects and data scientists to design and implement an offline and near real time analytics capability, visualization and a near real-time dash boarding and visualization capabilities to support Federal Agencies in strengthening their security posture against fraudulent web transactions to support Federal Agencies in strengthening their security posture against fraudulent transactions.
As part of the design and implementation effort, the data analytics developer will participate in various aspects of the implementation, including synthesizing large-scale system/communications logs, development of analytical data sets, and development of fraud models to identify anomalous transactions.
The Data Scientist will work closely with team members on the Data Science team and federal Government personnel.
- Identification of analytics approaches, and development of supporting analytical data sets.
- Development of fraud risk models based on features extracted from user application interactions, log transactions, network data, third party data, and other key data sources.
- Application of AI and ML techniques in developing and training fraud detection models, including application of graph analytics
- Development of integrated data sets, including the design and implementation of data integration across data analytics infrastructures as needed to support data analytics projects.
- Documentation of hypothesis, analytics approaches, and findings.
- Development of dashboards and reports to assess data performance and quality control.
- Assist with the development of project status briefings and dashboards for Agency executives
- Interact with senior client project team members and operational staff
- Must have a bachelor's degree + 18 years of experience, or Masters degree + 10 years of experience, or a PhD.
- Five or more years of experience developing production quality models.
- Extensive experience transitioning complex analytics environments to the cloud
- Highly focused, detail-oriented temperament are required.
- Experience in the design, development, integration, testing, and implementation of a large scale data sets
- Solid knowledge of Big data processing environments such as Hadoop, and tools/languages including Python, Scala, R, Spark, and Java
- Experience working in an AWS Cloud Environment is considered a plus
- Experienced user of Splunk or equivalent training in Splunk or other similar tool is considered a plus
- Experience with Neo4J (graph analysis) is considered a plus
- Strong analytic and creative problem solving abilities are required
- Highly inquisitive with an ability to work both independently and in collaborative setting
- Strong teamwork, communication and interpersonal skills
- Strong communication, written, and organizational skills
- Ability to work on multiple aspects of a large scale project which includes prioritizing, tracking, attention to detail, follow-up and follow-through to project completion
- Comprehensive knowledge and understanding of Internet web transactions, traffic flows are preferred.
- Applicants selected will be subject to a government public trust security investigation and must meet eligibility requirements for access to sensitive information.
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