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Agent Based Modeling Jobs in Quebec (NOW HIRING)

Design and execute model experiments, hypothesis testing, oracle testing, and statistical ... based retail applications. * Integrate multimodal vision capabilities into forecasting and AI agent ...

Administrative Assistant

Laval, QC · On-site

CA$20 - CA$25/hr

... AGENT THIS SUMMER! PRIVILEGES AND BENEFITS Our offices are located in Laval, and our working hours ... initiative underway, based on our customer experience model Accredited with honours by ...

... based config, deploy commands). * Solid understanding of the Model Context Protocol (MCP) or ... MCP servers, LLM tool registries, agent eval pipelines. * Familiarity with Figma's plugin/component ...

Design scalable data models required for the development of predictive models. * Ensure seamless ... Ability to design processes based on data flow concepts and architectures. * Ability to perform ...

Anyone can build an AI agent. What makes SAP's agents different is accuracy grounded in the richest ... Design and maintain enterprise ontologies and semantic models to improve interoperability, entity ...

Platform Architecture & Modeling: Design, build, and evolve the lakehouse data platform-reusable ... based on fit. * Snowflake Performance & Cost: Operate and tune Snowflake for reliability and ...

... based on their needs! Overview of what we offer: * Very competitive salaries * Flexible schedule ... Evaluate and select AI tools, models, and services, balancing capability, cost, and reliability

Showing results 21-40

Agent Based Modeling information

See Quebec salary details

$20K

$76.1K

$174K

How much do agent based modeling jobs pay per year?

As of Sep 7, 2026, the average yearly pay for agent based modeling in Quebec is $76,080.00, according to ZipRecruiter salary data. Most workers in this role earn between $40,000.00 and $100,000.00 per year, depending on experience, location, and employer.

What is an agent based modeling?

An Agent-Based Modeling (ABM) job involves developing and implementing simulations that model the interactions of autonomous agents within a system. These roles are common in fields like economics, epidemiology, traffic modeling, and artificial intelligence. Professionals in this role use programming and mathematical models to analyze complex systems and predict emergent behaviors. Key skills typically include coding (Python, NetLogo, or AnyLogic), data analysis, and knowledge of computational modeling techniques.

What are some typical challenges faced in an agent based modeling position?

A common challenge in Agent Based Modeling is accurately representing complex, real-world systems with diverse and dynamic agents while balancing computational resources and model simplicity. Professionals in this role often need to validate and calibrate their models with limited or imperfect data, requiring both technical skill and creativity. Additionally, effectively communicating modeling results to non-technical stakeholders and integrating feedback into iterations is a key part of the job. Overcoming these challenges provides rewarding opportunities to contribute to innovative solutions across areas like finance, healthcare, logistics, or social sciences.

What are the key skills and qualifications needed to thrive in the agent based modeling position, and why are they important?

To thrive in an Agent Based Modeling role, a strong background in computational modeling, mathematics, and systems analysis is typically required, often supported by a degree in computer science, engineering, or a related field. Proficiency with simulation tools such as NetLogo, AnyLogic, or Repast, as well as programming languages like Python or Java, is highly valuable. Effective communication, critical thinking, and strong collaboration skills help professionals explain complex models to stakeholders and work within multidisciplinary teams. These qualities are crucial for accurately simulating real-world systems, delivering actionable insights, and driving informed decision-making in various industries.

What are popular job titles related to Agent Based Modeling jobs in Quebec?

For Agent Based Modeling jobs in Quebec, the most frequently searched job titles are:

Infographic showing various Agent Based Modeling job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 13% Part Time, and 6% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $76,080 per year, or $36.6 per hour.

Data Product Steward - Data Office

Ts Imagine

Montreal, QC • On-site

Full-time

Medical, PTO

Posted 8 days ago


Job description

Role Overview We're looking for a Data Product Steward who's excited to sit at the intersection of financial-market data and AI - someone who cares as much about getting a definition exactly right as they do about seeing that definition come alive inside an AI agent's response. This role combines two closely connected responsibilities: end-to-end stewardship for assigned financial-data domains, and the development of Snowflake semantic layers and prompts that power AI-driven data products. You'll move fluidly between governing and improving data at the source and shaping how that data is structured, understood, and surfaced for AI agents and applications - helping turn complex financial data into something people and machines alike can trust.

You'll be a strong fit if you have: Experience in data management, data governance, or data stewardship, ideally in financial services / capital markets Working knowledge of Snowflake (or a comparable cloud data warehouse) and SQL Experience with at least one of: securities/instrument reference data, trading lifecycle data, risk or market data Interest or prior experience in prompt engineering, semantic modeling, or AI-agent enablement Strong communication skills - able to translate technical data concepts into clear business language for engineers, business stakeholders, and clients Responsibilities AI-Driven Data Product Development Build, maintain, and enhance semantic layers in Snowflake that provide the structure, definitions, relationships, and business context AI-driven products need Ensure data exposed through semantic layers is clearly defined, discoverable, consistent, and suitable for consumption by AI agents and applications Apply prompt engineering to develop, test, evaluate, and refine prompts and prompt patterns that improve accuracy, relevance, and consistency of AI-generated responses Translate complex financial-data concepts into semantic models, metadata, prompts, and instructions for AI-driven solutions Identify and close gaps in data, definitions, context, prompts, or user requirements that limit AI output quality Support agent reliability by ensuring AI outputs are grounded in accurate, well-governed data Data Stewardship & Domain Ownership Own end-to-end stewardship for assigned data domains: definition, documentation, governance, quality control, and continuous improvement Establish and monitor data-quality rules, controls, and KPIs (e.g., % fields with business definitions, SLA for issue resolution, quality-score trends) Investigate data-quality issues, drive root-cause analysis, and coordinate resolution with engineering and product teams Assess impact of proposed data changes on downstream consumers before they ship; perform QA/validation prior to production release Maintain documentation: business definitions, ownership, lineage, usage guidance, known limitations Act as the trusted point of contact for assigned domains, communicating data-quality risks, changes, and limitations proactively to stakeholders and clients L2 Support & Operations Serve as L2 support for data incidents, questions, and production issues within assigned domains Diagnose whether root cause is source data, transformation logic, business rules, or semantic definition Plan remediation for identified issues and communicate progress and impact clearly to related teams WHY TS IMAGINE. On-site role-4 days per week in our Montreal office, with 1 day of flexibility. Unlimited vacation + 3 personal days

Annual bonus and salary review. $1,500 training budget to fuel your growth. RRSP matching (3% company contribution).

Comprehensive health insurance. Subsidized public transportation (Opus & Cie). Note: This role is not remote-applicants must be based in Montreal.

ABOUT TS IMAGINE TS Imagine builds the technology the world's most sophisticated financial institutions rely on to trade across every asset class, manage risk in real time, and run their financing businesses. Execution, order management, risk, and financing all run on one platform with the same governed data foundation and proprietary ontology, giving clients a single trusted view of their business and actionable, explainable intelligence they can defend to regulators, counterparties, and compliance teams. Clients include global banks, asset managers, hedge funds, and prime brokers operating across equities, fixed income, FX, derivatives, and crypto.

TS Imagine delivers this through TSIQ: AI-powered intelligence grounded entirely in each client's own data. Headquartered in New York with 13 offices worldwide.