Overview Our client is looking for a data scientist to help with a project for approximately 10 hours per week, for at least six months. The work is fully remote, with team meetings during core business hours. The role is open to candidates anywhere in Canada. Responsibilities Drive key business outcomes such as customer retention, conversion, and product performance by designing and analyzing A/B tests, building predictive models (e.g., churn, pricing, recommendations), and applying statistical and machine learning techniques to extract insights from data. Partner cross-functionally to collaborate on analysis and recommendations. Work closely with data engineers to deploy and monitor models in production, automate pipelines, and translate complex outputs into actionable recommendations. Must-Have Skills Strong foundation in statistics, probability, and hypothesis testing. Proficiency in Python and analytical libraries (Pandas, NumPy, scikit-learn, StatsModels). Hands-on experience with SQL and at least one major data warehouse (Snowflake, BigQuery, Redshift, etc.). Experience designing and evaluating A/B experiments or other causal inference techniques. Experience with data visualization tools (Tableau, Power BI, Plotly, Streamlit, or similar). Experience with maturing industry tooling such as Azure AI Foundry Proven ability to translate complex analyses into clear, actionable insights for business audiences. Preferred Skills Experience with feature engineering and ML model lifecycle management. Familiarity with MLOps tools (MLflow, Airflow, Docker, dbt). Comfort with cloud environments (GCP, AWS, or Azure). Exposure to time-series forecasting, NLP, or anomaly detection. Master’s degree in Data Science, Statistics, Computer Science, or a related quantitative field. #J-18808-Ljbffr Akkodis group
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