Data Scientist, Business Intelligence, Reporting

This is a fully remote position, open to applicants in Canada.

📋 Description

• Collaborate with the Manager to define problems and take ownership of the development, validation, and delivery of solutions.

• Create and implement supervised learning models for both classification and regression tasks, encompassing feature engineering, selection, and tuning.

• Utilize clustering, segmentation, anomaly detection, and language models to address business challenges.

• Assist in enhancing time series forecasting initiatives.

• Design sampling strategies, experiments, and hypothesis tests to assess business inquiries and measure impact.

• Produce production-ready reusable Python code and frameworks for data preparation, model training, and evaluation.

• Construct data models to support analytics and internal products.

• Conduct validation and monitoring activities, including establishing baselines, backtesting, error metrics, and drift detection.

• Maintain documentation of work and version control to ensure reproducibility, auditing, and extensibility.

• Work in conjunction with Data Engineering and IT Infrastructure teams on data access, deployment, and production pipelines.

• Acquire data from warehouse tables, enterprise systems, APIs, flat files, Excel workbooks, and offline sources.

• Generate ad-hoc and regular analyses to address business queries.

• Convert analytical insights into metrics and reports utilized by business teams.

• Transform stakeholder inquiries into analytical challenges and deliver insights through storytelling, visualization, and recommendations.

• Facilitate the handover of delivered solutions via documentation and walkthroughs.

• Collaborate with Data Governance to enhance data quality and definitions.

• Prototype methodologies to boost efficiency, accuracy, or decision-making quality.

• Conduct experiments with established success criteria and communicate results.

• Stay updated on statistical, machine learning, and AI methodologies, assessing their practical applicability.

⛳️ Requirements

• Must be a resident of Canada.

• Bachelor’s degree in Computer Science, Data Science, Statistics, Economics, or a related quantitative discipline.

• At least 2 years of experience in statistical analysis, data science, or advanced analytics.

• Proficient in SQL, Python, and Git for analytics, statistical modeling, and machine learning.

• Experience in building, validating, and troubleshooting both supervised and unsupervised learning models, including classification, regression, and clustering.

• Strong understanding of statistical inference, hypothesis testing, and experimental design.

• Practical experience with GenAI or LLMs applied to real-world problems.

• Familiarity with time series forecasting methodologies.

• Experience with cloud data warehouses and business intelligence platforms.

• Proven ability to document and structure analytical work to ensure reproducibility and maintenance.

• Exceptional analytical and critical thinking skills.

• Effective communication abilities, capable of conveying complex concepts to varied audiences.

• High attention to detail and a dedication to analytical precision.

• Ability to independently manage multiple projects.

• Capacity to translate business requirements into analytical solutions.

• Flexibility to work extra or flexible hours when necessary.

• Occasional attendance at in-person meetings may be required.

• Preferred skills: Familiarity with AWS Redshift; Power BI, Tableau, or Looker; ERP source data, particularly SAP; experience in the recycling industry or regulated/reporting-intensive environments; Agile and sprint development experience.

🏝️ Benefits

• Opportunity to work remotely from a home office.

• Full-time salaried position.

• Flexible working hours on occasion.

• Reasonable accommodations provided during the recruitment and/or assessment processes.