Toronto, ON, CA
Live, first seen by us 10 days agoThe range described in this posting is an estimate by the Company, and may change based on several factors, including but not limited to a change in the duties covered by the job posting, or the credentials, experience or geographic jurisdiction of the successful candidate. Salary Range: $104,732-$150,000 Typical ExperienceRead the full posting
Turn supply chain bottlenecks into technical requirements for data scientists and engineers
Support planning and day-to-day management of data science and ML projects
Help design data pipelines and AI models tied to measurable business problems
Drive rollout and adoption of new AI tools and dashboards across supply chain teams
Track project milestones, KPIs, and ROI from deployed data initiatives
translating complex SCM business problems into clear technical requirements for data scientists and engineers
Support the planning, execution, and day-to-day management of data science and machine learning projects
Assist in the design and facilitation of data pipelines and AI models
Drive the rollout, adoption of new AI tools and dashboards across the supply chain organization
Monitor project milestones, track key performance indicators (KPIs), and report on the ROI and operational improvements generated by deployed data initiatives
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1. Core AI/ML Expertise: Deep, hands-on experience building models in Machine Learning (ML), Natural Language Processing (NLP), and Deep Learning. Proven capability working with Large Language Models (LLMs), Transformer architectures, and building RAG-based (Retrieval-Augmented Generation) applications to solve business problems. 2. Programming & Big Data: Expert-level proficiency in Python and PySpark for scalable data processing, data manipulation, and advanced analytics. Strong command of relational SQL databases 3. Data Engineering & MLOps: Advanced understanding of data engineering concepts, tool integration, and deploying scalable machine learning models using MLOps and CI/CD pipelines.
5. Data Visualization & Reporting: High proficiency in Power BI to build technical analytics dashboards that clearly communicate complex data insights, model performance, and ROI to operational leaders. 6. Cloud Proficiency (Multi-Cloud): Hands-on experience architecting and deploying AI solutions within Microsoft Azure (Databricks, Data Factory) and Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage) 7. Technical Agility: A demonstrated ability to quickly learn, adopt, and implement emerging languages, technical frameworks, and AI tools as the technology landscape evolves.
4. AI Integration & MCP Servers: Practical experience implementing the Model Context Protocol (MCP). Ability to configure, build, and manage MCP servers to securely and standardly connect AI models/agents with enterprise SCM data sources, internal operational tools, and external APIs 5. Data Visualization & Reporting: High proficiency in Power BI to build technical analytics dashboards that clearly communicate complex data insights, model performance, and ROI to operational leaders. 6. Cloud Proficiency (Multi-Cloud): Hands-on experience architecting and deploying AI solutions within Microsoft Azure (Databricks, Data Factory) and Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage)
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New Data Scientist postings at the employers we follow are down 4% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Req ID: 141441
Remote Position: Hybrid
Region: Americas
Country: Canada
State/Province: Ontario
City: Toronto
As a SCM Data Advisor, you will act as the crucial bridge between our Supply Chain Management operations and our advanced Data Science and AI teams. In this role, you will support the end-to-end lifecycle of Data Science and AI projects across all SCM processes. You will partner with cross-functional business leaders to identify operational bottlenecks, translate them into actionable AI/data initiatives, and help manage the successful delivery, deployment, and adoption of innovative supply chain solutions.
SCM AI Integration: Partner with supply chain domain experts to understand operational workflows and identify high-value technical opportunities where AI, machine learning, and data pipelines can optimize global SCM strategies.
AI & Data Project Support: Support the planning, execution, and day-to-day management of data science and machine learning projects, ensuring they align with overarching global SCM strategies.
Cross-Functional Translation: Bridge the communication gap by translating complex SCM business problems into clear technical requirements for data scientists and engineers.
Pipeline & Solution Facilitation: Assist in the design and facilitation of data pipelines and AI models, working hands-on with the team to ensure solutions are tailored to solve specific, measurable business problems.
Change Management & Adoption: Drive the rollout, adoption of new AI tools and dashboards across the supply chain organization, ensuring the business actually leverages the technology to achieve incremental results.
Performance Tracking: Monitor project milestones, track key performance indicators (KPIs), and report on the ROI and operational improvements generated by deployed data initiatives.
1. Core AI/ML Expertise: Deep, hands-on experience building models in Machine Learning (ML), Natural Language Processing (NLP), and Deep Learning. Proven capability working with Large Language Models (LLMs), Transformer architectures, and building RAG-based (Retrieval-Augmented Generation) applications to solve business problems.
2. Programming & Big Data: Expert-level proficiency in Python and PySpark for scalable data processing, data manipulation, and advanced analytics. Strong command of relational SQL databases
3. Data Engineering & MLOps: Advanced understanding of data engineering concepts, tool integration, and deploying scalable machine learning models using MLOps and CI/CD pipelines.
4. AI Integration & MCP Servers: Practical experience implementing the Model Context Protocol (MCP). Ability to configure, build, and manage MCP servers to securely and standardly connect AI models/agents with enterprise SCM data sources, internal operational tools, and external APIs
5. Data Visualization & Reporting: High proficiency in Power BI to build technical analytics dashboards that clearly communicate complex data insights, model performance, and ROI to operational leaders.
6. Cloud Proficiency (Multi-Cloud): Hands-on experience architecting and deploying AI solutions within Microsoft Azure (Databricks, Data Factory) and Google Cloud Platform (Vertex AI, BigQuery, Cloud Storage)
7. Technical Agility: A demonstrated ability to quickly learn, adopt, and implement emerging languages, technical frameworks, and AI tools as the technology landscape evolves.
8. Technical SCM Execution: Ability to leverage technical expertise to map end-to-end Supply Chain Management (SCM) processes to advanced technical solutions, acting as the lead technical architect on operational data projects.
The stated range includes Base Salary and target Short-Term Incentive (STI) compensation only. A comprehensive benefits package is offered in addition to this range.
The range described in this posting is an estimate by the Company, and may change based on several factors, including but not limited to a change in the duties covered by the job posting, or the credentials, experience or geographic jurisdiction of the successful candidate.
Salary Range: $104,732-$150,000
Prefer 5+ years of relevant supply chain experience and AI experience.
Post-secondary education or University Degree in Data Science, Machine Learning, Statistics, Mathematics, Computer Science, Analytics, or consideration of an equivalent combination of education and experience.
This job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.
Celestica is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, pregnancy, genetic information, disability, status as a protected veteran, or any other protected category under applicable federal, state, and local laws.
At Celestica we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. Special arrangements can be made for candidates who need it throughout the hiring process. Please indicate your needs and we will work with you to meet them.
COMPANY OVERVIEW:
Celestica, Inc. (NYSE: CLS; TSX: CLS) is a technology leader dedicated to driving customer success and market advancements. With deep expertise in design, engineering, manufacturing, supply chain, and platform solutions, Celestica enables critical data center infrastructure for AI, cloud, and hybrid cloud and advances technologies in high-growth markets. With a talented team and a strategic global network, Celestica helps its customers achieve competitive advantages.
Today, Celestica delivers innovative supply chain solutions globally to customers in strategic two operating and reporting segments: Advanced Technology Solutions (ATS) and Connectivity and Cloud Solutions (CC):
ATS: This segment serves customers in complex, regulated and high-reliability markets such as Industrial & Smart Energy, Aerospace & Defense, Semiconductor Capital Equipment, and HealthTech. It is engineering led, with deep expertise in design, manufacturing and lifecycle solutions.
CCS: This segment focuses on high-performance technology solutions and services for the data center, serving hyperscalers, digital native customers and enterprises. Celestica's Platform Solutions offering provides innovative and customizable computing, storage and networking solutions enabling AI-driven growth.
Built on a legacy of trust and performance, Celestica has earned its reputation by delivering results in complex and fast-changing markets. Celestica exceeds customer expectations by identifying trends and staying ahead of the curve. Backed by comprehensive capabilities and a global network across North America, Europe and Asia, Celestica helps customers gain competitive advantage with the quality, flexibility and resiliency they need to respond quickly to shifts in demand. Guided by a bold vision to accelerate market advancements, Celestica delivers innovative solutions and technologies that turn complexity into opportunity. Anchored in teamwork and commitment, Celestica strives to be the most trusted partner to its customers and colleagues worldwide.
We use artificial intelligence tools to assist in screening and assessing applications for this role. All hiring decisions involve human review.
This posting is for an existing vacancy.
Celestica would like to thank all applicants, however, only qualified applicants will be contacted.
Celestica does not accept unsolicited resumes from recruitment agencies or fee based recruitment services.
Selected passages from the saved posting. Check the full description for conditions and exceptions.
The range described in this posting is an estimate by the Company, and may change based on several factors, including but not limited to a change in the duties covered by the job posting, or the credentials, experience or geographic jurisdiction of the successful candidate. Salary Range: $104,732-$150,000 Typical Experience
Toronto, ON, CA
Req ID: 141441 Remote Position: Hybrid Region: Americas Country: Canada State/Province: Ontario City: Toronto Summary
COMPANY OVERVIEW: Celestica, Inc. (NYSE: CLS; TSX: CLS) is a technology leader dedicated to driving customer success and market advancements. With deep expertise in design, engineering, manufacturing, supply chain, and platform solutions, Celestica enables critical data center infrastructure for AI, cloud, and hybrid cloud and advances technologies in high-growth markets. With a talented team and a strategic global network, Celestica helps its customers achieve competitive advantages. Today, Celestica delivers innovative supply chain solutions globally to customers in strategic two operating and reporting segments: Advanced Technology Solutions (ATS) and Connectivity and Cloud Solutions (CC):
No clear work-authorization passage found. Eligibility is unconfirmed.