Data Scientist - Hybrid

Team: Data Science

Location: Oakville, Canada

Commitment: Full-Time

Workplace Type: hybrid

WHAT DOES THE DAY-TO-DAY LOOK LIKE

Build Predictive Weather Models: You will design, train, and deploy machine learning and spatio-temporal models to integrate weather feeds with client sales data to predicting demand, optimizing forecasts, and quantifying operational risk.

Derive Actionable Insights: You will conduct end-to-end exploratory analysis on complex meteorological datasets to uncover high-value patterns and translate probabilistic trends into strategic recommendations.

Drive B2B & Commercial Growth: You will partner with Sales, Marketing, and Customer Support to build analytics solutions for B2B initiatives.

Optimize ML Performance: You will leverage distributed frameworks (e.g., PySpark, Dask, Ray) and modern ML stacks (Scikit-learn, PyTorch/TensorFlow, LLMs) to improve model speed, scale inference pipelines, and lower compute costs.

Own the Model Lifecycle: Take responsibility for the full end-to-end lifecycle, including testing, deployment, and ongoing monitoring to ensure production-grade stability and reliability.

Technical documentation: Actively document model architectures, data lineage, and decision logic to ensure reproducibility, facilitate peer review, and maintain long-term institutional knowledge.

Cross-Functional Collaboration: You will partner closely with Data Engineers, Product Managers, and Revenue leaders to embed predictive algorithms into live APIs and deliver scalable data products that solve real-world enterprise problems.

WE ARE HOPING YOU HAVE

Degree in a STEM discipline (Data Science, Statistics, Computer Science, or a related quantitative field); a Master’s or PhD is preferred but not required. 

3+ years of data science experience specializing in B2B environments, with expertise in spatio-temporal modeling, time-series forecasting, and weather data intelligence. 

High proficiency in Google BigQuery (SQL, window functions, query optimization, and large-scale data manipulation).

Advanced expertise in Python for statistical modeling, data science, and graphical visualization (e.g., Matplotlib, Seaborn, or Plotly), with hands-on experience using core ML libraries including NumPy, SciPy, Scikit-learn, and TensorFlow or PyTorch. 

Experience working with distributed computing frameworks (e.g., Apache Spark) to process large-scale datasets. 

Strong communication skills, including the ability to explain complex ideas to an audience with a non-technical background 

NICE TO HAVE

• Proven experience developing and deploying Deep Learning models in industry or research environments. 

• Familiarity with deploying Large Language Models (LLMs) or retrieval-augmented generation (RAG) pipelines for automated reporting, intelligent customer support routing, or unstructured data processing. 

• Experience scaling models across large datasets using distributed processing frameworks.

 

DON’T MEET ALL THE REQUIREMENTS? DON’T WORRY…
Not all applicants will have skills that match a job description exactly. Pelmorex values and welcomes diverse experiences. While having “desired” qualifications makes for a strong candidate, we encourage applicants with alternative experiences to also apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Pelmorex. We are always looking for people who will be a culture add (yup, that's right, we don’t subscribe to culture fit, we want you to add to what we think is an amazing culture and work environment

INTERESTED? IT GETS BETTER….

Course Reimbursement Program 📚 We want you to keep learning, so we can too
Open and transparent communication, including All Hands Meetings with our CEO
Pelmorex Learning Academy 🏫
Your mental health is important to us! 🧠 We partner with our Benefits provider for virtual counseling sessions
Frequent employee pulse surveys 📝 we value your feedback so we can continue to make Pelmorex a great place to work!
Free online doctor visits 👩‍⚕️ with Maple Online Healthcare
While we encourage 1:1 conversations, we recognize that not everyone is comfortable with speaking up 🗣 We have an anonymous reporting platform to ensure everyone’s voice is heard