About the Job: We are
seeking a business-focused Data Scientist to use data science, advanced
analytics, Machine Learning, and AI to generate insights, improve customer
experience, optimize operations, and support strategic decision-making across
business functions. The ideal candidate will combine strong technical skills
with business understanding and the ability to work closely with business,
product, data engineering, and technology teams.
Office Location: Toronto
Employment Type: Permanent
Role Type: New position –
current requirement
Work Arrangement: Hybrid (2
days in office per week)
Position Responsibilities:
Predictive Modeling &
Forecasting: Design, train, and validate robust traditional
machine learning models and advanced time-series forecasting algorithms (e.g.,
for demand planning, inventory optimization, and sales forecasting).
End-to-End GCP Deployment: Architect
and productionize scalable predictive pipelines leveraging Google
Cloud Platform (e.g., BigQuery, Vertex AI). Transition models from
local/development environments to highly optimized, automated cloud
deployments.
Data Wrangling &
Processing: Ingest, organize, and manipulate billions of rows of data
from dozens of disparate sources using highly efficient SQL and Python scripts
to ensure data quality and model reliability.
Business Partnership &
Insights: Act as a strategic bridge between technical and
non-technical teams. Translate complex model outputs into actionable business
strategies, presenting findings, test results, and performance analyses to
senior management.
Mentorship & Leadership: Provide technical
guidance, code reviews, and architectural support to junior data scientists and
ML engineers, navigating complex real-world business problems on a case-by-case
basis.
Continuous Innovation: Constantly
upskill and remain fully updated with the evolving data and analytics
community, integrating new traditional ML techniques and exploring
emerging technologies.
Requirements
- 5+ years of applied industry experience in data
science, statistical analysis, and machine learning.
- Ph.D. or Master's degree in Computer
Science, Mathematics, Statistics, or a related quantitative field.
- Deep expertise in traditional machine
learning algorithms (regression, classification, clustering, tree-based models)
and a strong specialization in forecasting techniques (e.g., ARIMA, Prophet,
exponential smoothing).
- Advanced, production-level programming skills
in Python (Pandas, Scikit-Learn, Statsmodels)
and highly complex SQL for large-scale data manipulation.
- Strong, hands-on proficiency in the
Google Cloud Platform ecosystem. Experience building, training, and deploying
models using Vertex AI, BigQuery, and Google Cloud Storage.
- Exceptional ability to distill complex data into
meaningful business insights. Effective written and verbal communication skills
are mandatory for cross-functional collaboration.
Preferred Qualifications:
- Knowledge or hands-on experience with Deep Learning
architectures and Generative AI (e.g., LLMs, building Retrieval-Augmented
Generation (RAG) pipelines).
- Previous experience applying data science
within the retail sector (e.g., supply chain forecasting, pricing
optimization, customer lifetime value).
- Familiarity with containerizing workloads (Docker)
and using orchestration tools (like Google Cloud Composer / Apache
Airflow) to schedule and trigger complex ML training pipelines.
- Familiarity with tracking and documentation tools
such as JIRA and Confluence.
Benefits
Salary Range: CAD $100,000
- $115,000/year
The final compensation offered
will depend on local market conditions and geographic location, as well as
job-related factors such as the candidate’s knowledge, skills, qualifications,
relevant experience, and education/training. Compensation may also include
additional components such as benefits, and/or other incentives, where
applicable. In accordance with new employment standards requirements, we retain
copies of this job posting and applicant information for three (3) years after
the posting is removed. We do not use AI technology; all applications are also
reviewed by our recruitment team.
Infoya is an equal opportunity
employer committed to diversity and inclusion. We welcome applications from all
qualified individuals, regardless of race, color, religion, sex, sexual
orientation, gender identity, national origin, age, disability, protected veteran
status, aboriginal status, or any other legally protected factors.
Skills Required
- 5+ years of applied industry experience in data science, statistical analysis, and machine learning.
- Ph.D. or Master's degree in Computer Science, Mathematics, Statistics, or a related quantitative field.
- Deep expertise in traditional machine learning algorithms (regression, classification, clustering, tree-based models) and forecasting techniques (ARIMA, Prophet, exponential smoothing).
- Advanced, production-level programming skills in Python (Pandas, Scikit-Learn, Statsmodels).
- Highly complex SQL for large-scale data manipulation.
- Strong, hands-on proficiency in Google Cloud Platform including Vertex AI, BigQuery, and Google Cloud Storage for model building, training, and deployment.
- Exceptional written and verbal communication skills for cross-functional collaboration and presenting to senior management.
- Knowledge or hands-on experience with Deep Learning architectures and Generative AI (LLMs, RAG pipelines).
- Previous experience applying data science within the retail sector (supply chain forecasting, pricing optimization, CLV).
- Familiarity with containerization (Docker) and orchestration/scheduling tools (Google Cloud Composer / Apache Airflow).
- Familiarity with tracking and documentation tools such as JIRA and Confluence.
What We Do
Infoya is a global IT solutions and consulting firm specializing in business transformation, digital innovation, and advanced engineering services, including AI and cloud enablement.









