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Algorithmic Trading Jobs in Quebec (NOW HIRING)

A drive to grow and learn, curiosity, passion for the trade and the desire to meet challenges. The ... tool or Algorithms. Familiarity and working knowledge with Spine will also be beneficial.

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Algorithmic Trading information

What is algorithmic trading?

Algorithmic trading involves trading in equities, currencies, or other financial instruments using computer programs. A trading program uses an algorithm to calculate current market conditions. This trading method is automated, so the program buys or sells the financial instrument when the algorithm says that the market meets all the requirements for a profitable trade. To create an algorithm, you perform mathematical and statistical analysis, also known as quantitative analysis, on an exchange or equity. After creating an algorithm with defined trading rules, you test it using historical market data. While this is primarily a technical field, you also need an understanding of the market.

What is algorithmic trading?

Algorithmic trading refers to the use of computer programs and algorithms to automatically execute trading orders in financial markets. These algorithms follow predefined rules based on factors like price, timing, and volume to optimize trading strategies and reduce human intervention. Algorithmic trading is widely used by institutional investors, hedge funds, and individual traders to increase efficiency, minimize costs, and capitalize on market opportunities. It can range from simple rule-based systems to complex strategies involving machine learning and artificial intelligence.

What are the key skills and qualifications needed to thrive as an algorithmic trader, and why are they important?

To thrive as an Algorithmic Trader, you need a strong background in quantitative analysis, programming (often Python, C++, or Java), and a solid understanding of financial markets, typically supported by a degree in mathematics, engineering, finance, or computer science. Familiarity with statistical modeling tools, trading platforms, and backtesting systems is essential, and certifications such as CFA or FRM can be advantageous. Superior problem-solving skills, attention to detail, and the ability to work under pressure set standout professionals apart in this field. These skills are crucial to developing, implementing, and refining trading strategies that can operate profitably and reliably in fast-moving financial environments.

What are the main challenges faced by professionals in algorithmic trading, and how can they be addressed?

Professionals in algorithmic trading often encounter challenges such as developing strategies that remain effective in rapidly changing markets, minimizing latency for faster execution, and managing the risks associated with automated trading systems. To address these challenges, it's essential to stay updated with the latest market trends and technological advancements, conduct rigorous backtesting of algorithms, and implement robust risk management protocols. Collaboration with quantitative analysts, software engineers, and risk managers is also key to ensuring strategies are both innovative and resilient.

What is the difference between Algorithmic Trading vs Quantitative Analyst?

AspectAlgorithmic TradingQuantitative Analyst
Required CredentialsDegree in finance, computer science, or related field; programming skillsDegree in mathematics, statistics, or finance; strong analytical skills
Work EnvironmentTrading firms, hedge funds, financial institutions; fast-pacedInvestment banks, asset management firms; research-focused
Employer & Industry UsageUsed to automate trading strategiesDevelops models to inform trading decisions

While both roles involve quantitative skills and finance knowledge, Algorithmic Traders focus on implementing automated trading systems, whereas Quantitative Analysts develop models and strategies that may be used by traders or firms. The roles often overlap but differ mainly in their primary focus: execution versus modeling.

What are popular job titles related to Algorithmic Trading jobs in Quebec?

For Algorithmic Trading jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Algorithmic Trading jobs in Quebec look for?

The top searched job categories for Algorithmic Trading jobs in Quebec are:

Infographic showing various Algorithmic Trading job openings in Quebec as of August 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Remote job distribution.

Geospatial Data Engineer

Shearwater Aerospace

Montreal, QC โ€ข On-site, Remote

Full-time

Re-posted 19 days ago


Job description

We're Building Autonomous Flight Intelligence

Drones that think for themselves. Not pre-programmed routes-true autonomy where aircraft make intelligent decisions onboard, adapting to weather, obstacles, and airspace in real-time without human intervention.

We're building weather-aware flight optimization that delivers outcome-driven autonomy for the real world-increasing mission success by extending range, endurance, safety, and reliability.

You'll architect the geospatial brain that makes this possible

The Opportunity

You'll be our first geospatial hire, building the data processing systems that enable autonomous flight decisions. Working with our CTO, you'll architect how our systems evolve from initial implementation to production-grade infrastructure that handles real-world operational demands.

What you'll own:
  • Design geospatial processing pipelines that balance performance, accuracy, and extensibility
  • Build GIS analysis algorithms for weather-aware route optimization
  • Integrate multi-source datasets (elevation, obstacles, airspace, meteorological models)
  • Create APIs that enable real-time flight decision-making
  • Establish patterns and tooling that evolve as our platform matures

Why this matters: Operators deploy missions in challenging conditions. Your work directly determines whether autonomous systems can navigate safely, optimize for changing weather, and complete objectives-or get grounded.

You Might Be a Fit If...

You think in trade-offs.
You can explain why you chose PostGIS over alternative spatial databases, or when to pre-process vs. compute on-demand. You know the geospatial database landscape and select tools based on requirements, not trends. You're comfortable defending your decisions and pivoting when new constraints emerge.

You stay current and execute rigorously.
You follow modern geospatial best practices and understand OGC standards. You keep up with evolving tools and approaches instead of relying on outdated tooling.

You've shipped production GIS systems.
You've wrestled with coordinate transformations, spatial indexing, and raster processing. You know the common GIS tools and libraries-GDAL/OGR, various spatial databases, processing frameworks-and understand when each fits. Bonus: you've worked with meteorological data (NetCDF, GRIB) or atmospheric models.

You're comfortable with ambiguity.
Requirements evolve. Priorities shift. You ask clarifying questions, propose solutions, and deliver incrementally rather than waiting for perfect specs.

You communicate clearly.
You can explain technical trade-offs to non-engineers and translate vague product needs into concrete implementation plans. Ego doesn't enter the room when someone questions your approach.

Technical Foundation We're Looking For

Core GIS competency:

  • 4+ years building geospatial software (or 3 years if you've shipped impressive systems)
  • Strong knowledge of common GIS tools and libraries (QGIS, GDAL/OGR)
  • Experience with geospatial algorithms (visibility analysis, spatial operations, terrain analysis)
  • Deep understanding of coordinate systems, projections, and spatial data structures

Python ecosystem:

  • Strong Python with scientific computing stack (NumPy, Pandas, SciPy)
  • Geospatial libraries: GeoPandas, Rasterio, Xarray, Dask

Data infrastructure:

  • Experience with spatial databases (PostGIS, Apache Sedona, etc)
  • Comfortable with cloud infrastructure (GCP preferred), Docker, Git
  • Ability to set up automated data ingestion workflows

Nice to have:

  • C/C++ for performance-critical processing
  • Meteorology, atmospheric science, or aviation background
  • Degree in GIS, Computer Science, Engineering, or related field. Master's is a plus, but we'll prioritize what you've built over credentials.
What We Offer

Equity ownership - You're building foundational systems. You should own a meaningful piece of what we're creating.

Architectural influence - This isn't "implement the spec." You'll shape technical decisions alongside the CTO as we define what autonomous flight infrastructure looks like.

Hybrid flexibility - Work where you're most productive. We're in Montreal but value focus time and thoughtful collaboration over face-time.

Growth with the platform - You'll evolve systems as we mature from initial architecture to production-hardened infrastructure. The foundations you establish will scale with increasing mission complexity, data volumes, and operational demands-and you'll architect that evolution.

Direct impact - Your code runs onboard aircraft making critical flight decisions. You'll see your work enable missions that weren't possible before, extending operational capabilities in real-world conditions.

Apply

We're looking for problem-solvers who thrive when building systems from first principles in a domain that matters.

Strong foundation in geospatial engineering but don't check every box? We want to hear from you. We value learning agility and problem-solving ability over credential collection.

Employment Type: FULL_TIME