• Us Citizen

• Green Card

• EAD (OPT/CPT/GC/H4)

• H1B Work Permit

• Corp-Corp

• Consulting/Contract

• UG :- - Not Required

• PG :- - Not Required

• No of position :- ( 1 )

• Post :- 27th Nov 2020

• Prepare data science business cases while working with domain experts and customers. Support defining the AI strategy within a federal government agency.
• Independently develops customized algorithms to solve analytical problems with incomplete data sets and implements automated processes for efficiently producing scale models.
• Independently conducts statistical modelling, machine learning modelling and experiment design, and tests and validates predictive models.
• Perform statistical analysis, data mining, temporal and pattern analysis, correlation of events, predictive modelling, and pattern recognition.
• Document and visualize analytics both temporally and spatially, and present analytic results and uncertainty to decision makers.
• Provide informational briefings to explain methodologies and analytical findings to peers and customer stakeholders.
• Investigate and implement new scientific analysis and methodologies to support big data analytics efforts and implement workflows, data models, indexes and templates and facilitate data movement on all associated systems and networks.
• Provide architecture analysis and design implementation with detailed technology roadmaps and transition planning and master plans as required.
• Finds and recommends new uses for existing data sources; designs, modifies, and builds new data processes; and builds large, complex data sets.

Other similar professional duties maybe assigned as needed.

Requirements:

• 5 to 8 years of experience with programming languages (such as Python, R, Java, Ruby, Spark, or SQL), and statistical analytics (such as SAS, Matlab, R).
• 3 to 5 years of experience with machine learning and deep learning modelling (with packages such as TensorFlow, Keras, PyTorch, etc.)
• Experience in analysis, processing, tagging, and indexing unstructured, semi-structured, and structured classified and unclassified data sets.
• Experience developing research designs, including formulating testable questions, identifying and defining key concepts and variables, and matching appropriate methods to problems
• Experience in data management, including cleaning and preparing data, and creating, structuring, and maintaining data sets
• Experience with incorporating data science capability into Stakeholder strategy
• Experience bridging data science strategy between leadership, IT, data scientists and other stakeholders.
• Good understanding of Databases, SQL, Hadoop, Hive and/or MapReduce

• PhD (preferred) or master’s in data science, Mathematics, Analytics, Statistics or related field will take precedence for interviews.