About the role
We are hiring a Senior Data Scientist on behalf of a well-established organization in Toronto to join their team on a 6-month contract with a possibility of further extension.
As a Senior Data Scientist, you will design, develop, and deploy scalable machine learning and forecasting models. In this role, you will own the end-to-end lifecycle of data science projects—from complex data extraction and exploratory analysis to model training, evaluation, and production deployment on Google Cloud Platform (GCP). You will operate at the intersection of traditional ML, advanced time-series forecasting, and cloud infrastructure, building reliable, high-performance solutions that process billions of rows of data. Your work will directly inform short- and long-term strategic decision-making, drive retail innovation, and continuously improve through automated pipelines and data-driven evaluation.
Key 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.
Required Qualifications/Skills:
5–10 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. Core ML & Forecasting Mastery: 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). Programming Mastery: Advanced, production-level programming skills in Python (Pandas, Scikit-Learn, Stats models) and highly complex SQL for large-scale data manipulation. GCP Infrastructure: Strong, hands-on proficiency in the Google Cloud Platform ecosystem. Experience building, training, and deploying models using Vertex AI, BigQuery, and Google Cloud Storage. Communication & Critical Thinking: Exceptional ability to distill complex data into meaningful business insights. Effective written and verbal communication skills are mandatory for cross-functional collaboration.
Nice to Have Qualifications:
Advanced AI / GenAI: Knowledge or hands-on experience with Deep Learning architectures and Generative AI (e.g., LLMs, building Retrieval-Augmented Generation (RAG) pipelines). Retail Domain Expertise: Previous experience applying data science within the retail sector (e.g., supply chain forecasting, pricing optimization, customer lifetime value). MLOps & Orchestration: Familiarity with containerizing workloads (Docker) and using orchestration tools (like Google Cloud Composer / Apache Airflow) to schedule and trigger complex ML training pipelines. Agile Tools: Familiarity with tracking and documentation tools such as JIRA and Confluence.
Travel Requirements:
Travel to SSC Toronto at minimum once a month, or when required.
Working Conditions:
Working in an office setting: computer work, camera on virtual meetings. Work overnights and weekends on occasion to support system upgrades, model deployments, and critical project rollouts
Not the right fit? Search for Data Scientist jobs in North York, Ontario, Canada
About Hays
We are leaders in specialist recruitment and workforce solutions, offering advisory services such as learning and skill development, career transitions and employer brand positioning.
As the Leadership Partner to our customers, we invest in lifelong partnerships that empower people and businesses to succeed. We help you achieve your career goals and deliver your business needs by combining meaningful innovation with our global scale and insights.
Last year we helped over 280,000 people find their next career. Join the millions of people around the world that our specialist recruitment consultants provide with up-to-date information on career options, interesting insights and specific industry trends.
We help our customers define and implement strategies to create inclusive and equitable workplaces. Through harnessing and analysing data, we support business decision making and advise on how to access Talent Networks. We also assist in identifying attractive employer propositions by truly understanding a company’s identity, and support clients with all aspects of their Early Careers proposition, from strategic planning through to operational execution.
Hays is the market leader in the UK and Asia Pacific and one of the market leaders in Continental Europe and Latin America. The c.12,800 people we employ around the world partner with clients and candidates to power the world of work. Every day our expert consultants help thousands of candidates find their next role, and they also help clients reshape workforces and deal with talent shortages. In the year to 30 June 2021, we placed 77,000 people in permanent jobs and 244,000 people into temporary roles. For more information about our global network, strategy and Group financial results, visit www.haysplc.com
Similar Jobs
About the role
We are hiring a Senior Data Scientist on behalf of a well-established organization in Toronto to join their team on a 6-month contract with a possibility of further extension.
As a Senior Data Scientist, you will design, develop, and deploy scalable machine learning and forecasting models. In this role, you will own the end-to-end lifecycle of data science projects—from complex data extraction and exploratory analysis to model training, evaluation, and production deployment on Google Cloud Platform (GCP). You will operate at the intersection of traditional ML, advanced time-series forecasting, and cloud infrastructure, building reliable, high-performance solutions that process billions of rows of data. Your work will directly inform short- and long-term strategic decision-making, drive retail innovation, and continuously improve through automated pipelines and data-driven evaluation.
Key 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.
Required Qualifications/Skills:
5–10 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. Core ML & Forecasting Mastery: 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). Programming Mastery: Advanced, production-level programming skills in Python (Pandas, Scikit-Learn, Stats models) and highly complex SQL for large-scale data manipulation. GCP Infrastructure: Strong, hands-on proficiency in the Google Cloud Platform ecosystem. Experience building, training, and deploying models using Vertex AI, BigQuery, and Google Cloud Storage. Communication & Critical Thinking: Exceptional ability to distill complex data into meaningful business insights. Effective written and verbal communication skills are mandatory for cross-functional collaboration.
Nice to Have Qualifications:
Advanced AI / GenAI: Knowledge or hands-on experience with Deep Learning architectures and Generative AI (e.g., LLMs, building Retrieval-Augmented Generation (RAG) pipelines). Retail Domain Expertise: Previous experience applying data science within the retail sector (e.g., supply chain forecasting, pricing optimization, customer lifetime value). MLOps & Orchestration: Familiarity with containerizing workloads (Docker) and using orchestration tools (like Google Cloud Composer / Apache Airflow) to schedule and trigger complex ML training pipelines. Agile Tools: Familiarity with tracking and documentation tools such as JIRA and Confluence.
Travel Requirements:
Travel to SSC Toronto at minimum once a month, or when required.
Working Conditions:
Working in an office setting: computer work, camera on virtual meetings. Work overnights and weekends on occasion to support system upgrades, model deployments, and critical project rollouts
Not the right fit? Search for Data Scientist jobs in North York, Ontario, Canada
About Hays
We are leaders in specialist recruitment and workforce solutions, offering advisory services such as learning and skill development, career transitions and employer brand positioning.
As the Leadership Partner to our customers, we invest in lifelong partnerships that empower people and businesses to succeed. We help you achieve your career goals and deliver your business needs by combining meaningful innovation with our global scale and insights.
Last year we helped over 280,000 people find their next career. Join the millions of people around the world that our specialist recruitment consultants provide with up-to-date information on career options, interesting insights and specific industry trends.
We help our customers define and implement strategies to create inclusive and equitable workplaces. Through harnessing and analysing data, we support business decision making and advise on how to access Talent Networks. We also assist in identifying attractive employer propositions by truly understanding a company’s identity, and support clients with all aspects of their Early Careers proposition, from strategic planning through to operational execution.
Hays is the market leader in the UK and Asia Pacific and one of the market leaders in Continental Europe and Latin America. The c.12,800 people we employ around the world partner with clients and candidates to power the world of work. Every day our expert consultants help thousands of candidates find their next role, and they also help clients reshape workforces and deal with talent shortages. In the year to 30 June 2021, we placed 77,000 people in permanent jobs and 244,000 people into temporary roles. For more information about our global network, strategy and Group financial results, visit www.haysplc.com