Int. Data Science Developer

Source Code; Toronto; Hybrid; CAD 70,000 - 90,000; Full time

Job summary

A leading tech firm in Toronto is seeking an Intermediate Data Science Developer to analyze systems requirements and implement cloud-based data products. The role demands 2-5 years of experience in data science or analytics and proficiency in Python, SQL, and visualization tools. The candidate will work hybrid until October 2025, transitioning to full onsite by January 2026, and will collaborate with IT among other responsibilities.

Qualifications

• 2-5 years of experience in data science, analytics, or related field.
• Proven experience in data analysis, visualization, and statistical modeling.
• Ability to clean, transform, and manage large datasets using Python, R, or SQL.

Responsibilities

• Participate in product teams to analyze systems requirements.
• Design, create, and maintain cloud-based data lake and lakehouse structures.
• Conduct reviews, resolve operational problems, and support business partners.

Skills

Data analysis

Data visualization

Statistical modeling

Python

SQL

Big Data frameworks (Apache Spark, Hadoop)

Job description

About the job RQ09863 - Int. Data Science Developer

RQ09863 - Int. Data Science Developer

Toronto (222 Jarvis or 159 Sir William Hearst) -Hybrid:

- From October 20, 2025, the candidate is required to work onsite 4 days a week and 1 day from home

- From January 5, 2026, the candidate is required to work onsite 5 days a week fully

Participate in product teams to analyze systems requirements, architect, design, code and implement cloud-based data and analytics products that conform to standards. Design, create, and maintain cloud-based data lake and lakehouse structures, automated data pipelines, analytics models, and visualizations (dashboards and reports). Liaises with cluster IT colleagues to implement products, conduct reviews, resolve operational problems, and support business partners in effective use of cloud-based data and analytics products. Analyses complex technical issues, identifies alternatives and recommends solutions. Prepare and conduct knowledge transfer

Must Have:

• 2-5 years of professional experience in data science, data analytics, or a related quantitative field (e.g., data engineering, machine learning, or business intelligence) or equivalent.
• Proven experience in data analysis, visualization, and statistical modeling for real-world business or research problems.
• Demonstrated ability to clean, transform, and manage large datasets using Python, R, or SQL.
• Python (pandas, NumPy, scikit-learn, statsmodels, matplotlib, seaborn)
• SQL (complex queries, joins, aggregations, optimization)
• Experience working with big data frameworks such as Apache Spark Hadoop for large-scale data processing.