Role Overview
Bell is hiring a mid-level Data Scientist II-Agentic AI. This is a full-time role in Mississauga, Ontario. Part of Bell's Data Science hiring. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job Description
Category
Technology
Job Id
427850
- *Req Id:** 427850
Connection is everything. It drives us to innovate, explore, and stay close to what matters to us most. At Bell, we’re building a more connected future through world-class networks, AI-powered solutions, and digital experiences that elevate how people live, work, and play every day.
We believe in empowering people. That’s why we equip our teams with cutting-edge technology, AI tools, and a collaborative environment that supports creativity and growth. Want to be part of a diverse team where your work makes a real impact? If you’re inspired by innovation that advances how people connect and transforms what’s possible, you belong on #TeamBell.
## **Summary**
We are seeking a highly motivated and analytical Data Scientist II- Agentic AI to join our team. The ideal candidate will have a strong foundation in data science principles, experience working with LLMs, and a passion for developing impactful AI solutions. The team focuses on solutions that improve technical troubleshooting /support for technicians and customers. This role offers the opportunity to work on innovative, high-impact data products within a collaborative team environment. You will contribute to the architecture, development, and deployment of cutting-edge AI-powered applications, collaborating within our expert team and gaining practical experience from senior mentorship.
## **Key Responsibilities**
- Design and implement single and multi-agent systems that can reason, plan, and act to solve complex user problems.
- Define agent behavior, memory, and tool-use strategies with a strong emphasis on correctness, controllability, and user experience.
- Implement AI protocols and frameworks such as ADK/Langchain for A2A orchestration
- Integrate agents with internal/external systems (knowledge bases, ticketing, diagnostics) via APIs, MCP, and tool orchestration.
- Design persistent memory and state management for multi-turn dialogue
- Build guardrails, safety logic, and human-in-the-loop escalation paths — critical for a support domain where agents' advising is required.
- Develop frameworks for evaluation and observability (LLM as a judge, test cases, agent evaluations, tracking agent quality over time)
- Optimize system performance by analyzing model behavior and failure modes, turning qualitative issues into measurable signals for improvement.
## **Critical Qualifications**
- Bachelor's degree in computer science, Data Science, Engineering, Applied Math, or related fields. Relevant experience may be considered in lieu of a degree.
- 3+ years of relevant work experience in data science and/or machine learning.
- Advanced proficiency in SQL and Python.
- Ability to write clean, efficient, and reusable code.
- Agentic or RAG systems experience: You've built at least one system involving tool use, retrieval-augmented generation, multi-step reasoning, or autonomous agents — not just single-shot completions.
- Hands-on LLM experience: You've worked directly with LLM APIs (OpenAI, Gemini, Anthropic, etc.) and understand the practical realities — prompt design, context management, latency, cost, and failure modes.
- Agile Mindset & Collaboration: Proven experience delivering literately, collaborating in a team environment, communicating clearly.
## **Preferred Qualifications**
- Master’s degree in a discipline such as Computer Science, Data Science, Engineering, Applied Math, or related field.
- Certification in cloud-based data platforms and services (e.g., GCP).
- Familiarity with agent frameworks (LangGraph, CrewAI, ADK, etc).
- Experience in a Cloud environment (GCP is preferred, but cloud skills are transferable) and building agentic workflows.
- Exposure to modern DevOps and ML Ops practices, including CI/CD, containerization, and orchestration.
- Domain experience in tech support or knowledge management systems.
Adequate knowledge of French is required for positions in Quebec.
- *Additional Information:**
- *Position Type:** Management
- *Job Status:** Regular - Full Time
- *Job Location:** Canada : Ontario : Toronto || Canada : Ontario : Mississauga
- *Work Arrangement:** Hybrid
- *Application Deadline:** 04/17/2026
For work arrangements that are ‘Hybrid’, successful candidates must be based in Canada and report to a set Bell office for a minimum of 3 days a week. Recognizing the importance of work-life balance, Bell offers flexibility in work hours based on the business needs.
- *Please apply directly online to be considered for this role. Applications through email will not be accepted.**
We know that caring for our team members is at the heart of a healthy, positive and thriving workplace. As part of o
Frequently Asked Questions
How do I apply for the Data Scientist II-Agentic AI position at Bell?
Use the Apply button above to submit your application directly to Bell. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Data Scientist II-Agentic AI position at Bell located?
This position is based in Mississauga, Ontario. Bell has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Data Scientist II-Agentic AI at Bell earn?
Bell has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Data Scientist II-Agentic AI role at Bell posted?
This role was posted on April 5, 2026 (64 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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