REMOTE - Data Science Analyst

Reporting to the Director, Analytics & Insights, the Data Analyst enables better, faster and simpler decisions through data and science. They generate valid, reliable and timely insights for business operations and strategic initiatives, drive go-to-market tactics through effective performance analysis and ensures that internal customers’ needs are met, and that operational excellence is improved and maintained.

The Data Analyst works closely with the rest of the analytics team to build & maintain tools & processes that enable the manipulation and transformation of data across multiple platforms. They have the mandate to automate processes and imbed data science principles to enhance decision making processes. They meet with stakeholders to gather business requirements, translate them into technical requirements, execute development deliverables, test functionalities, address ad-hoc requests, execute data related standard operating procedures and manage stakeholder expectations along the way. Additionally, the Data Analyst builds, maintains and enhances reports and dashboards as part of their business intelligence responsibilities. Finally, the Data Analyst commits to enhancing customer experience and identifies plans and executes continuous improvement endeavors accordingly.
Analysis & reporting
Understand and capture business needs from stakeholders to analyze and track the performance of their activities.
Develop statements of work to secure buy-in from stakeholders regarding analysis methods, timelines, roles & responsibilities and deliverable formats
Develop new, enhance and maintain reports and dashboards in Tableaus.
Generate valid and reliable insights by designing analysis methodologies and executing analysis projects that are repeatable and that produce statistically significant results.
Address ad-hoc reports and analysis requests.
Data management and quality assurance
Build processes to manipulate, transform and extract insights from datasets across various types of data sources using Python & Pandas
Troubleshoot and perform root case analysis activities to resolve technical challenges and recommend scalable solutions
Formulate, maintain, and enhance ETL pipelines
Migrate databases from local servers into cloud data warehouses (AWS, Azure Databricks)
Transform, refactor, and deploy ETL & ML models to production level in a virtual or cloud-based system (AWS, Azure Databricks)
Assemble large datasets from various data sources for prescriptive and predictive analytics
Flag data integrity issues and execute quality assurance procedures.

Bachelor’s Degree specializing in Business Administration, Economics, Computer Science, Analytics, Computer Engineering, Information Systems, Applied Math/Statistics, or related fields.

• Master’s degree is an asset (MBA, MSc, MMA, etc.).
• Can analyze large data sets from multiple sources through efficient database tools & methods
• Experience in understanding departmental needs and in building effective, positive partnerships to work collaboratively with cross-functional business teams (technical and non-technical stakeholders).
• Advanced proficiency with Python, SQL, etc.
• Knowledge of Python ML Libraries such as Sci-kit Learn and TensorFlow
• Experience with big data tools like Apache Spark, Pandas and Polars
• Knowledge of cloud-based systems like AWS, Azure and development tools like Git, Bash are a plus
• Advanced working knowledge with relational SQL and NoSQL databases i.e. Knowledge of Tableau
• Is flexible and can adapt quickly to an ever-changing environment.
• Hybrid Work Setting - The flexibility to work remotely or in the office enhances work-life balance and strengthens our sense of Brother Community and Team Spirit. #