Sr Data Analyst

Base pay range: CA $90,000.00/yr - CA$/yr

Hybrid — 5 days a week in office but possible 2 days per week WFH with Manager's approval.

The Senior Data Analyst will serve as a highly skilled and motivated member of our team.

The ideal candidate will bring 3–5 years of professional experience applying analytics, statistical modelling, and advanced data techniques to solve complex business problems.

This role involves end-to-end data science work — from data gathering and preparation to advanced modelling and deployment — to deliver actionable insights and predictive capabilities.

You will collaborate closely with business stakeholders, data engineers, and analysts to design, implement, and optimize data-driven solutions.

A strong background in statistical analysis, data mining, linear programming/optimization, and predictive modelling is required, along with proficiency in translating data into strategic recommendations.

Looking for potential candidates who have experience in finance, banking, manufacturing, engineering, or construction, or a similar industry.

• 3–5 years of professional data science experience, including analytics, model development, and deployment in a business environment.
• Proven track record in predictive modelling, optimization, and statistical analysis.

• Strong proficiency in Python or R for statistical analysis and modelling.
• Solid knowledge of SQL for data querying and manipulation.
• Experience with machine learning libraries (e.g., scikit-learn, Tensor Flow, PyTorch) and statistical packages.
• Familiarity with optimization tools (e.g., PuLP, Gurobi, CPLEX) is highly desirable.
• Proficiency in data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn).
• Strong understanding of relational databases and big data platforms (e.g., Spark, Hadoop) is a plus.

• Develop, implement, and maintain statistical and machine learning models to address business challenges.
• Conduct advanced statistical analyses, including regression, hypothesis testing, time-series forecasting, and multivariate analysis.
• Apply data mining and pattern recognition techniques to identify trends, anomalies, and actionable insights.
• Use linear programming and optimization methods to improve operational efficiency and decision-making.

• Collaborate with data engineering teams to ensure robust data pipelines and efficient data structures.
• Source, clean, and validate data from multiple internal and external sources.
• Ensure the integrity, accuracy, and quality of datasets used for modelling.

• Partner with stakeholders to understand business needs and translate them into analytical projects.
• Present results and recommendations clearly and concisely to technical and non-technical audiences.
• Research and apply new methodologies, tools, and technologies to enhance modelling capabilities.
• Stay current on advancements in data science, AI/ML frameworks, and best practices.
• Drive continuous improvement in processes, tools, and analytical frameworks.

Education

• Strongly Preferred:
  Advanced degree (e.g., Master’s, etc.) in Applied Mathematics, Statistics, Computer Science, Data Science, Operations Research, or related field.
• Minimum Requirement:
  Bachelor’s degree in a data science/quantitative discipline with relevant experience.

Mid-Senior level

Full-time

Information Technology

IT Services and IT Consulting