1 день назад
Data Scientist (AI)
Мэтч & Сопровод
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Описание вакансии
Текст:
TL;DR
Data Scientist (AI) (Python/BigQuery/PyTorch): Building predictive weather and commercial data models that integrate weather feeds with client sales data to forecast demand, quantify operational risk, and optimize advertising performance with an accent on spatio-temporal modeling, time-series forecasting, and scalable machine learning. Focus on deploying and monitoring production-grade model lifecycles, scaling inference with distributed frameworks, and embedding predictive algorithms into live APIs.
Location: Hybrid work at the Oakville, Canada location; candidates must be eligible to work in Canada
Company
develops weather intelligence and commercial data products, including The Weather Network.
What you will do
- Design, train, and deploy predictive weather, spatio-temporal, and time-series models using weather feeds and client sales data.
- Analyze complex meteorological datasets and translate probabilistic trends into strategic recommendations.
- Develop analytics solutions for B2B initiatives, with occasional contributions to B2C and Adtech initiatives.
- Optimize machine learning performance and inference pipelines with distributed frameworks such as PySpark, Dask, and Ray.
- Own testing, deployment, monitoring, documentation, and the full lifecycle of production models.
- Collaborate with Data Engineers, Product Managers, Sales, Marketing, Customer Support, and Revenue leaders to embed algorithms into live APIs and scalable data products.
Requirements
- 3+ years of data science experience in B2B environments, including spatio-temporal modeling, time-series forecasting, and weather data intelligence.
- Degree in Data Science, Statistics, Computer Science, or another quantitative STEM discipline.
- Advanced Python skills for statistical modeling, data science, and visualization.
- High proficiency in Google BigQuery and SQL, including window functions, query optimization, and large-scale data manipulation.
- Experience with NumPy, SciPy, Scikit-learn, TensorFlow or PyTorch, and distributed computing frameworks such as Apache Spark.
- Strong communication skills and the ability to explain complex concepts to non-technical audiences.
Nice to have
- Experience developing and deploying deep learning models.
- Experience deploying LLMs or retrieval-augmented generation pipelines.
- Experience scaling models across large datasets with distributed processing frameworks.
Culture & Benefits
- Flexible hybrid work environment.
- Retirement savings matching plan, personal spending account, summer hours, and paid time off.
- Course reimbursement and access to the Learning Academy.
- Virtual mental health counseling and free online doctor visits.
- Open communication, employee pulse surveys, an inclusion and diversity team, and anonymous reporting.
Hiring process
- Interviews are designed to provide a fair and authentic assessment based on the candidate’s own experience and thinking.
- Real-time AI assistance and automated response tools are not permitted during interviews.
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