Data Analytics Specialist

The successful candidate will be a Data Analytics Specialist / Data Scientist with a diverse range of analytical skills and experience in working in multi-faceted roles. The role may have aspects of any or all the following: data analysis, data science, data modelling, statistical analysis, artificial intelligence (AI) & machine learning (ML), strategizing, advising, data product design and delivery. There may be aspects of data engineering, technical analysis, and business analysis.

Duties:
Provides hands-on support, leadership, advice and direction on the strategic data initiatives that are being undertaken as part of the Data Strategy. A critical responsibility is to coordinate with various internal and external clients to understand their analytics needs and how to use the data to best meet these needs. This resource is an expert in anticipating, identifying and responding to diverse and complex data analytic requirements across departments and from external organizations, while also aligning with other areas of branch and broader department. Services and project deliverables should evolve as the work progresses, in response to emerging user and business needs, as well as design and technical opportunities.

Works with Manager Analytics Capability Centre to:

• Develop and share analytical models and products.
• Provide continuous improvement of analytics capacities.
• Design and support development of analytic service offerings.
• Analyze and organize raw data, preparing it for prescriptive and predictive modeling, while building algorithms that deliver business value.
• Support in development of full-stack data analytics or AI applications as required.
• Provide expertise and leadership in the design and competition of analytic projects.
• Evaluating business needs, enhancing data quality, and designing analytical tools to support our data services.
• Conducting complex data analysis and collaborating with data engineers and analysts on various projects.
• Coaching and mentorship team members, fostering a client-centric approach and encouraging innovative solutions.
• Working closely with senior management to support a cultural shift toward data as a strategic asset and maintain effective relationships with internal and external stakeholders.
• Create and present options, roadmaps, frameworks, models, and briefings for senior executives with regards to analytics services, based on best and emerging practices and principles.
• Facilitate strategic conversations to develop shared understanding and generate options for decision-making to align diverse stakeholder interests and goals.
• Develop baseline and ongoing outcomes, key results, metrics, and other indicators.
• Work as part of a team responsible for the generalizable extraction of knowledge from data by applying various techniques and methodologies including probability models, machine learning, computer programming, statistics, data engineering, pattern recognition and learning, and data visualizations
• Apply skills to provide insights, support decision-making and facilitate strategic business planning across the department.
• Requires a focus on understanding predictive analytics and needs-based analytics strategies to simplify, consistently produce and re-use analytical models and assets to drive measurable value.
• Provide executives and decision-makers with a deeper understanding of their operations, transactions, services and information required for them to identify new opportunities that can be uncovered through analytics.
• Provide depth and insights on data assets and transform them into meaningful analytics for decision making
• Bring knowledge of statistical classification techniques such as k-means and hierarchical clustering, partition trees, and logistic regression.
• Integrate both quantitative and qualitative data to create business insights.
• Design and create dashboards and custom reporting with various data sources and inputs.
• Analyze data and prepare results.
• Gather and document client requirements.
• Capture business and technical metadata for analytical products.
• Escalate issues and risks, as appropriate.
• Work within a multi-vendor/staff environment.

• Experience and comprehensive skills in using statistical and computer languages, e.g. R, Python, SQL
• Experience in building analytical and quantitative analysis models.
• Experience in preparing data for prescriptive and predictive modelling
• Experience in understanding complex businesses questions and framing the right analytical question to solve a business problem.
• Experience with and understanding of different approaches and methods for data analytics and data science (e.g. complex statistical modelling).
• Experience with and understanding of statistical and data mining techniques to address key business issues.
• Experience with Artificial Intelligence (AI) or Machine Learning (ML) applied to data science or analytics, such as using ML for anomaly detection, predictive monitoring, or AI-assisted data transformation and automation.

• Experience and knowledge of data sharing, data-linkage, de-identification, metadata, data quality, ethics, synthetic data and data literacy and how to promote use of government data.
• Experience building and deploying end to end analytical or AI enabled applications, from data ingestion and modeling through to user facing solutions using modern web frameworks (e.g., React.js, Vue.js, or similar), enabling intuitive consumption of data and insights.
• Experience combining raw data from a variety of data sources within and across domains.
• Experience dealing with clients and explaining complex data principles in a thoughtful manner.
• Experience designing and maintaining data pipelines, data analytics workflows, or data product workflows.
• Experience preparing visualizations, dashboards, and analytical models
• Experience utilizing big data technologies (e.g., Hadoop, Spark) or cloud platforms (e.g. Azure, Snowflake)
• Experience working with large government datasets.