Job Description
Description
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Looking for a skilled Data Scientist on a contract basis to support a Toronto-based marketing analytics team in optimizing marketing investments through robust modelling, analytics, and actionable insights. This role will focus on the development, deployment, and adoption of advanced models to evaluate marketing campaign performance and drive strategic decision-making.
Key Responsibilities:
- Develop and deploy statistical and machine learning models to measure the impact of marketing campaigns and optimize spend across short- and long-term business objectives.
- Lead and contribute to complex, end-to-end projects, often operating in ambiguous environments with tight timelines.
- Help shape the team’s roadmap by identifying and prioritizing high-impact projects.
- Think creatively and critically to solve both scientific and practical business problems, ensuring insights are adopted by stakeholders.
- Collaborate cross-functionally with Data Scientists, Engineers, Analysts, and Marketing stakeholders to integrate models into business processes.
Ideal Candidate Profile:
- Bachelor’s or Master’s degree in a STEM field (e.g., Computer Science, Data Science, Mathematics).
- 3+ years of hands-on experience building and productionizing machine learning/statistical models.
- Advanced proficiency in Python and SQL; experience with Databricks is a strong asset.
- Strong foundation in statistical methodologies, including Bayesian inference, time series analysis, multilevel modeling, double ML, and bootstrapping.
- Proven ability to integrate data science solutions into operational workflows.
- Organized, self-motivated, and capable of leading projects with minimal supervision.
- Excellent communication skills, with the ability to translate technical concepts for both technical and non-technical stakeholders.
Seniority level
- Mid-Senior level
Employment type
- Contract
Job function
- Information Technology
Industries
- Staffing and Recruiting
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Company
Forsyth Barnes
Location
Toronto
Country
Canada
Salary
150.000
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