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Global Pharma Tek

Data Science Developer

ON, Canada
Ontario, Canada, Canada

Contract

Apply About employer

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Job details

Job type: Contract
Apply by: Dec 5, 2026
Working hours: 36.25 hours/week
Posting language: English
Posted: Nov 5, 2026

Original job description

Job-Role/Title: Data Science /Data Engineer Developer
Job-Type: Contract Opportunity - 6-month term
Possibility of Extensions: Yes, optional extension of 6 months.
Job Location: Toronto, ON - M5V 2X4, Canada | Hybrid Work - 3 days/week in the office.
Work Hours: 7.25 Hours a Day or 36.25 hours/week, Monday to Friday

Ideal Resource for this Role / Must-Have Experience & Skills:

Advanced hands-on expertise in Python, software engineering, LLMs, RAG, agentic AI, APIs, prompt engineering, model evaluation, and production AI development.
Strong hands-on experience with Microsoft Foundry/Azure AI Foundry, Azure Machine Learning, Azure AI services, and cloud-based AI solution development.Tech stack: Python, SQL, LLM, Power Automate, VSCode, Git, Jira, Azure (mainly OpenAI, Copilot Studio and Foundry), Databricks.
Strong technical foundation in statistics and machine learning, including classification, regression, clustering, feature engineering, model evaluation, and ML pipelines, with demonstrated ability to develop solutions that achieve measurable performance.

Position Overview: The Data Science Developer will design, develop, and implement enterprise AI solutions, including Generative AI applications, intelligent agents, and reusable AI components. The role will accelerate delivery of priority AI use cases and establish reusable capabilities that reduce reliance on one-off solutions and external resources.

Key Responsibilities & Deliverables:

Design, develop, test, and implement GenAI applications, intelligent agents, and AI-enabled solutions for priority business use cases.
Build reusable AI components, services, APIs, and solution patterns that can be leveraged across multiple business areas.
Develop solutions using large language models (LLMs), retrieval-augmented generation (RAG), agentic AI, machine learning, and related AI techniques.
Integrate AI solutions with enterprise data sources, applications, APIs, and business workflows.
Develop prototypes and proofs of concept and evolve successful solutions toward secure, scalable, production-ready implementations.
Partner with Product Managers, Data Scientists, Data Engineers, Data Architects, and business teams to translate requirements into working AI solutions.
Apply software engineering practices including version control, testing, documentation, CI/CD, monitoring, and performance optimization.
Evaluate AI solution performance, reliability, accuracy, and scalability and continuously improve implemented solutions.
Incorporate Responsible AI, privacy, security, and data governance requirements into solution design and development.
Contribute to reusable enterprise AI patterns, development standards, technical documentation, and knowledge transfer to strengthen internal AI capability.

NOTE: Demonstrated deliverables from current and previous contracts may be provided as formal documents, review comments, working-session outputs, annotated artifacts, decision notes, issue logs, or other written outputs accepted.

Key Qualifiers:

Public Sector Experience: preferred but not required
Degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or a related discipline, or equivalent experience.
Significant experience in AI, machine learning, data science development, or software engineering.
Strong programming skills, particularly Python and SQL, with experience developing production-quality applications.
Experience developing solutions using LLMs, GenAI, RAG, AI agents, machine learning, and APIs.
Experience integrating AI solutions with enterprise applications and data platforms.
Knowledge of cloud-based AI platforms, software development practices, APIs, Git, CI/CD, testing, and monitoring.
Understanding of prompt engineering, model evaluation, Responsible AI, security, privacy, and AI governance.
Strong analytical, problem-solving, communication, and collaboration skills.

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More about this job

Responsibilities

Design, build, test, and deploy generative AI applications, intelligent agents, and reusable AI components integrated with enterprise data, applications, APIs, and workflows. Evaluate and improve production solutions while applying software engineering, security, privacy, Responsible AI, and governance practices, and collaborating with technical and business teams.

Requirements

Requires significant experience in AI, machine learning, data science development, or software engineering, with strong Python and SQL skills and experience delivering production-quality solutions using LLMs, RAG, AI agents, APIs, and cloud AI platforms. A degree in computer science, data science, engineering, artificial intelligence, or a related discipline - or equivalent experience - is specified, along with knowledge of software development, CI/CD, testing, monitoring, model evaluation, and Responsible AI.

Skills

Python
SQL
Software Engineering
Large Language Models
Retrieval-Augmented Generation
Agentic AI
Prompt Engineering
Machine Learning
Microsoft Azure AI Foundry
Azure Machine Learning
Azure AI Services
API Development
Model Evaluation
Git
CI/CD
Databricks

Visa sponsorship

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Keywords

Python
SQL
Large Language Models
Generative AI
Retrieval-Augmented Generation
Agentic AI
Intelligent Agents
Prompt Engineering
Machine Learning
Classification
Regression
Clustering
Feature Engineering
Model Evaluation
Machine Learning Pipelines
Microsoft Azure AI Foundry
Azure Machine Learning
Azure AI Services
Microsoft Copilot Studio
Power Automate
Databricks
Visual Studio Code
Git
Jira
APIs
CI/CD
Responsible AI
Data Governance
Cloud-Based AI
Software Engineering

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