Overview
A top Canadian enterprise is seeking a skilled **Data Scientist** to join its growing analytics and AI team. This role involves solving complex business problems using data-driven approaches, machine learning, and predictive modeling. The company offers flexibility to work remotely or from major cities like Toronto or Vancouver.
Job Title: Data Scientist
Company: Confidential (Example: RBC, Shopify, IBM, Telus, etc.)
Location: Toronto / Vancouver / Remote, Canada
Job Type: Full-Time, Permanent
Salary Range: CAD $90,000 – $125,000 per year
Industry: Artificial Intelligence / Data Analytics / Technology
Remote Option: Yes (Remote / Hybrid Available)
Key Responsibilities
- Analyze large datasets to discover insights, patterns, and trends.
- Develop machine learning models for classification, prediction, and segmentation.
- Collaborate with product managers, analysts, and engineers to define data requirements.
- Implement algorithms in Python or R and deploy models in production environments.
- Clean, structure, and validate data from various sources (SQL, APIs, cloud).
- Communicate findings through dashboards, reports, and visualizations.
- Contribute to data governance and model monitoring processes.
Required Skills and Qualifications
Essential Qualifications
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or equivalent.
- 2+ years of experience as a Data Scientist or in a related role.
- Proficiency in Python, R, SQL, and popular ML libraries (e.g., scikit-learn, pandas, TensorFlow).
- Hands-on experience with cloud platforms like AWS, Azure, or Google Cloud.
- Strong knowledge of statistical analysis and predictive modeling.
- Experience with BI tools such as Tableau, Power BI, or Looker.
- Ability to translate business questions into data science solutions.
Preferred (Bonus) Qualifications
- Experience working in banking, healthcare, telecom, or retail analytics.
- Familiarity with big data tools like Spark, Hadoop, or Databricks.
- Knowledge of NLP, recommender systems, or time-series analysis.
- PhD in a quantitative field (optional but valuable).
- Experience deploying models using MLOps or CI/CD pipelines.
Application Process
- Visit the company’s careers portal or apply via LinkedIn Jobs.
- Upload your resume and optional cover letter.
- Complete an online assessment or case study (if required).
- Prepare for virtual interviews focused on technical skills and business thinking.
- Finalists may be asked to present a past project or portfolio.
Documents Required
- Resume (PDF format)
- Cover letter (optional but helpful)
- Portfolio or GitHub (with Jupyter notebooks or ML projects)
- Academic degree certificate(s)
- ID proof (Government-issued)
- References or recommendation letters (if requested)