Service Innovation and Performance Department, Service Transformation, Service Analytics and Planning Branch
1 Full-time Continuous Position - 35.00 hours/week
Affiliation: CIPP
Salary: $85,232.42 to $103,707.24 annually (2016 rates of pay)
Category: Current Opportunities
Employment Group: Other
Responsible for providing technical oversight and leading solutions development that involve applying scientific hypothesis and modeling complex data (unstructured, numeric and non-numeric) to guide business decisions through the use of cognitive science, statistical, algorithmic, mining and visualization techniques. The Data Scientist serves as the department's technical subject matter expert on assigned solutions, provides ongoing oversight for the roadmap for the assigned solutions, and leads quality assurance and due diligence activities.
Completion of a Master's Degree in Mathematics, Applied Statistics, Physics, Computer Science/Engineering or a related quantitative discipline
Minimum 8 years of experience working in a leading role with data and/or quantitative analysis in a data collection, statistical, analytical and performance measurement function, including at least 3 years of experience working in a leading role with statistical and predictive modelling concepts, artificial intelligence/machine learning algorithms, Big Data platforms, data capture from multi-dimensional sources and collaboration within multi-functional teams
Demonstrated experience must include:
experience leading and executing sophisticated data mining & modeling solutions
experience as a technical leader and subject matter expert on a skilled team of data and analytics professionals
proficiency in developing scientific hypotheses, statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and optimization algorithms
experience using statistical packages such as R, Python MATLAB, SPSS, SAS
experience in data preparation and data integration techniques and tools
experience with programming languages like Java, Scala, Python and R and cloud computing technologies
*Experience and formal training combined with demonstrated performance and ability may substitute for stipulated academic requirements.
English oral, reading, writing
In depth knowledge of the advanced technologies common to the data mining & machine learning world such as: techniques such as clustering, classification, regression analysis and optimization algorithms; big data frameworks such as Hadoop, Spark; BI visualization tools such as Tableau, MS Power BI, Qlik, etc.
Geographic information systems (GIS) to capture, store, manipulate, analyze, manage, and present spatial or geographic data
How to develop and recommend solutions to loosely defined business problems by leveraging pattern detection over potentially large datasets
Computer literacy utilizing MS Office software applications
Knowledge of applicable health and safety legislation, including the rights and duties of workers
Demonstrated ability to communicate insight gained though use of stories with compelling visual elements
Demonstrated ability to quickly understand new concepts and to provide original solutions to mathematical issues
Passion for data and analytics and commitment to staying current with new technologies and innovative approaches and enabling their use to help clients achieve their goals and solve business problems
Highly refined analytical and problem solving skills; ability to anticipate scenarios and develop solution options
Demonstrated written and verbal communication skills to communicate effectively on technical and non-technical matters with key stakeholders and lead project teams
Demonstrated ability in corporate core competencies including customer service, communication, team work, initiative/self management, accountability, flexibility and adaptability
Ability to manage multiple priorities in a fast-paced, ever changing environment
Self-directed and organized; able to manage responsibilities for multiple, simultaneous projects
Work effectively as a lead and team member within a multi-disciplinary environment
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