Data Scientist

at  Law Society of Alberta

The Law Society of Alberta (“Law Society") regulates the legal profession in the public interest. In alignment with the Law Society’s vision, mission, and strategic plan, the Applications and Information (A&I) department provides Information Governance, Technology and Organizational Change Management services for the organization to both protect and enable efficient business operations. The A&I department supports three distinct but related entities: the Law Society, the Alberta Lawyers Indemnity Association (“ALIA”) and the Canadian Centre for Professional Legal Education (“CPLED”).
The Data Scientist role is responsible for harnessing the power of data to enhance our regulatory efforts by designing, developing, and maintaining data solutions. The role combines the skills of data science, such as data analysis, machine learning, and visualization, with the skills of data architecture, such as data modeling, data engineering, and data governance. The role will collaborate with stakeholders across the organization to understand their data needs, provide insights, and deliver scalable and reliable data products.

QUALIFICATIONS:

• Bachelor’s degree in data science, computer science, statistics, or related discipline.
• At least 7 years of experience in data science, data architecture or data engineering roles.
• Skilled in data science techniques, such as data mining, data analysis, machine learning, natural language processing, and deep learning.
• Strong knowledge and experience with data architecture principles, such as data modeling, data engineering, data quality, and data governance.
• Ability to analyze complex data sets and derive actionable insights.
• Strong skills in integrating data from various sources to achieve desired outcomes of the business.
• Experience in designing scalable and efficient data architectures.
• Solid understanding of data security best practices and protocols
• High proficient communicator both verbally and in writing. Must be able to clearly present data insights to non-technical stakeholders in a clear and concise manner.
• Must be able to gather requirements and elicit business needs effectively and collaboratively with business stakeholders.
• Must be able to manage work independently including multiple competing priorities and timelines.
• Ability to mentor or coach non-technical users in how to use reporting dashboards or tools so that they can perform their own data analysis where possible.
• Expert level knowledge of Power BI is required. Knowledge of Tableau and other similar tools is also an asset
• Proficiency in SQL is mandatory. Experience with Python, R, C++ or other languages is an Experience with Microsoft Dataverse, Graph and Fabric is desirable.

The Data Scientist will be a senior resource in the Data Analytics team and responsible for business intelligence, data science, data architecture or engineering and data governance. Responsibilities will include:

• Collaborating with business stakeholders to define data requirements and needs
• Managing data analytics projects from requirements definition through transitioning the solution into use or operations.
• Analyzing organizational data to identify trends and patterns.
• Developing predictive models and algorithms that may assist the business to make data-driven decisions.
• Designing and implementing data pipelines, data warehouses, data lakes, and/or data marts using cloud-based technologies and best practices.
• Developing and applying data science methods, such as statistical analysis, machine learning, natural language processing, deep learning and artificial intelligence, to solve business problems and generate insights.
• Creating and maintaining data models, data dictionaries, data catalogs, and data quality rules to ensure data consistency, accuracy, and accessibility.
• Building and deploying data applications, dashboards, and reports using various tools and frameworks to communicate and visualize data findings and recommendations.
• Researching and evaluating new data technologies, trends, and best practices to improve data capabilities and performance. Continually learning, developing and staying current with evolving methods and practices.
• Implementing data governance processes and standards to ensure data integrity, security, privacy, and compliance.
• Identifying methods to protect sensitive data through robust security measures in collaboration with other members of the A&I team.