The Data Scientist SME (DSS) will act as lead over other data scientists and data analysts. The DSS will leverage tools such as ServiceNow, JIRA, or similar ITSM tools to monitor and review team member assignments to ensure equitable use of resources, and to exercise quality control over tasks.
Meet with their team members daily in SCRUM fashion (10 mins) to provide an opportunity to hear risks and will mitigate as necessary.
Responsible to ensure team members coordinate across teams as necessary to ensure more complex tasks successful, and to ensure team members embrace skill enhancement through mentoring and on-the-job training moments.
Solutions requiring new software, methodologies, approaches, or other changes will be coordinated with the task lead and SME forums to ensure that all solutions are in compliance, and are within the constraints of the ATO. Solution stack baselines (a list of pre-approved software and code) will be encouraged to eliminate unnecessary changes to baselines.
Involved in the analysis of unstructured and semi-structured data, including latent semantic indexing (LSI), entity identification and tagging, complex event processing (CEP), and the application of analysis algorithms on distributed, clustered, and cloud-based high-performance infrastructures.
Exercises creativity in applying non-traditional approaches to large-scale analysis of unstructured data in support of high-value use cases visualized through multi-dimensional interfaces.
Handle processing and index requests against high-volume collections of data and high-velocity data streams.
Has the ability to utilize advance tools and computational skills to interpret, connect, predict and make discoveries in complex data and deliver recommendations for business and analytic decisions.
Experience with machine learning, algorithm analysis, and data clustering. Work with visualization specialist to ensure output is captured to help understand complex problems.
Work with junior Data Scientist to elevate skills for breath and depth in the field.
REQUIRED QUALIFICATIONS:
Requires BA/BS and 15+ years of experience, preferably with a minimum of four years of management experience.
Leading over other data scientists and data analysts.
Experience ensuring team members coordinate across teams as necessary to ensure more complex tasks successful, and to ensure team members embrace skill enhancement through mentoring and on-the-job training moments.
Working with unstructured and semi-structured data, including latent semantic indexing (LSI), entity identification and tagging, complex event processing (CEP), and the application of analysis algorithms on distributed, clustered, and cloud-based high-performance infrastructures.
Demonstrated experience exercising creativity in applying non-traditional approaches to large-scale analysis of unstructured data in support of high-value use cases visualized through multi-dimensional interfaces.
Has used advance tools and computational skills to interpret, connect, predict and make discoveries in complex data and deliver recommendations for business and analytic decisions.
Machine learning, algorithm analysis, and data clustering. Work with visualization specialist to ensure output is captured to help understand complex problems.
Ability to work with junior Data Scientist to elevate skills for breath and depth in the field.
