[Hiring] Data Scientist @Circular Materials

Role Description

Reporting to the Manager, Data Science, the Data Scientist designs and delivers statistical, machine learning, and AI solutions that turn business problems into measurable improvements. The Data Science team is small and project-based that supports business processes across the organization while increasingly leaning into experimentation.

• Proficient in Python and SQL.
• Versed in predictive modeling, statistical inference, and time series.
• Familiar with modern ML and analytics workflows (feature engineering, validation, experiment design, and monitoring).
• Sharp attention to detail and a commitment to reproducibility through clear documentation, version control, and repeatable code.

This is a full-time, salary paid position, which requires residency in Canada.

Responsibilities

• The Data Scientist works with the Manager to scope problems, then owns the build, validation, and delivery of the solution.
• Statistical Modeling and Machine Learning
  • Design and implement supervised learning models for classification and regression, including feature engineering, selection, and tuning.
  • Apply clustering, segmentation and anomaly detection techniques to identify patterns and unusual behaviour in data.
  • Apply language models to problems such as classification, extraction, and intelligent document processing where they outperform conventional methods.
  • Support and extend the team's time series forecasting work.
  • Design sampling approaches, experiments and hypothesis tests to evaluate business questions and quantify impact.
• Solution Development and Delivery
  • Take scoped problems through to delivered solutions.
  • Develop production-quality, reusable Python code and frameworks for data preparation, model training, and evaluation.
  • Develop data models supporting analytics and internal products.
  • Treat validation and monitoring as part of delivery, including baselines, backtesting, error metrics, and drift detection for models in ongoing use.
  • Document work and maintain version control to a standard that lets another person run, audit, and extend it.
  • Work with Data Engineering and IT Infrastructure on data access, deployment, and the transition of validated work into production pipelines.
• Data Analysis and Reporting
  • Source data for analysis and experimentation from curated warehouse tables, enterprise source systems, APIs, flat files, and offline sources including Excel workbooks.
  • Produce ad-hoc and recurring analysis that answers specific business questions.
  • Translate analytical findings into the metrics and reporting business teams use to make decisions.
• Collaboration and Communication
  • Work with business stakeholders to turn business questions into analytical problems.
  • Present complex statistical concepts and insights through clear storytelling, visualization, and business-focused recommendations.
  • Act like an owner by following work through to a delivered outcome, surfacing risks and open questions early rather than waiting to be asked.
  • Support the handover of delivered solutions, including documentation and walkthroughs for the teams that will operate them.
  • Work with Data Governance to improve the quality and definitions of the data the team relies on.
• Continuous Improvement
  • Identify business processes where a new method could improve efficiency, accuracy, or decision quality, and prototype it to show whether it works.
  • Run experiments with success criteria defined up front, and report clearly on results.
  • Stay current with emerging statistical, machine learning, and AI methods and assess them for practical fit.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Statistics, Economics or a related quantitative field.
• Minimum of 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 building, validating, and diagnosing supervised and unsupervised learning models (classification, regression, clustering) for business problems.
• Solid understanding of statistical inference, hypothesis testing, and experimental design.
• Hands-on experience applying GenAI or LLMs to practical problems.
• Exposure to time series forecasting methods.
• Experience working with cloud data warehouses and BI platforms.
• Experience documenting and structuring analytical work so that others can reproduce and maintain it.

Assets

• Hands-on experience with AWS Redshift.
• Hands-on experience with Power BI, Tableau, or Looker.
• Experience working with ERP source data, particularly SAP.
• Prior working experience in the recycling industry, or in regulated and reporting-heavy environments (EPR, utilities, public sector, finance).
• Agile and sprint development experience.

Knowledge/Competencies/Skills

• Exceptional analytical and critical thinking abilities.
• Strong communication skills with ability to explain complex concepts to diverse audiences.
• High attention to detail and commitment to analytical accuracy.
• Self-motivated with ability to manage multiple projects independently.
• Proven ability to translate business needs into analytical solutions.

Working Conditions

• All CM employees work 40 hours per week, remotely from a home office environment.
• Extra or flexible hours may be required on occasion.
• Occasional in-person meetings may be required.

Pay Transparency

Expected Compensation: An annual base salary in the range of $70,000 to $85,000. The actual salary offered will be determined within the range, and will depend on factors, such as the candidate’s unique qualifications, relevant experience, work location and expected contributions.

Job Vacancy Reason

This position is a new position.

Applicant and Interviewee Communication

We thank all applicants for their interest. However, only those under consideration will be contacted. Applicants who have been interviewed will be informed whether a hiring decision has been made within 45 days of their final interview.

Record Retention

Job posting records and associated application forms will be retained for at least three years.