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Python Data Analysis Jobs in Montreal, QC (NOW HIRING)

Conducting rigorous exploratory data analysis to uncover patterns, anomalies, and opportunities ... Expert-level proficiency in Python and/or R; you write clean, maintainable, production-quality code

The Analytics team is responsible for developing Poka's data analytics platform and managing a wide ... You will also work on production-grade Python code for backend services and integrations, and ...

Analytical Skills: Ability to design and implement effective solutions to complex problems ... Usage of LLM models for application, Agentic implementation, usage of tools to integrate data into ...

Provide strategic recommendations based on data analysis to support decision-making processes ... R, Python, GitHub. * Team spirit: Strong enthusiasm for collaborative teamwork. * Problem-solving:

Strong programming skills in Python and experience with popular machine learning libraries such as TensorFlow, PyTorch and scikit-learn * Solid understanding of statistical analysis, data mining ...

Make strategic recommendations based on data analysis to support decision-making processes.a * ross ... Python and GitHub. * Machine Learning Expertise: Deep understanding of machine learning theories ...

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Python Data Analysis information

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$22.9K

$103.9K

$187.5K

How much do python data analysis jobs pay per year?

As of Jun 12, 2026, the average yearly pay for python data analysis in Montreal, QC is $103,933.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,332.00 and $139,107.00 per year, depending on experience, location, and employer.

What is a Python Data Analysis job?

A Python Data Analysis job involves using Python programming to collect, clean, analyze, and visualize data for insights and decision-making. Professionals in this role use libraries like Pandas, NumPy, and Matplotlib to manipulate datasets and perform statistical analysis. They may work in various industries, solving business problems, identifying trends, and supporting data-driven strategies. Strong programming skills, data wrangling expertise, and knowledge of analytical techniques are essential for success in this field.

What are the key skills and qualifications needed to thrive in the Python Data Analysis position, and why are they important?

To thrive in a Python Data Analysis role, you need strong proficiency in Python programming, statistical analysis, and data wrangling, often backed by a degree in computer science, mathematics, or a related field. Familiarity with tools such as Pandas, NumPy, Jupyter Notebook, and visualization libraries like Matplotlib or Seaborn, along with potential certifications in data analysis or Python, is highly valuable. Analytical thinking, attention to detail, and effective communication help translate complex data findings into actionable insights for stakeholders. These capabilities are crucial for transforming raw data into meaningful information that supports business decision-making.

What are the typical responsibilities of someone working in Python Data Analysis?

Professionals in Python Data Analysis are usually responsible for collecting, cleaning, and analyzing datasets to uncover trends and inform business strategies. Their daily tasks often include writing Python scripts, visualizing data, conducting statistical analyses, and preparing reports that summarize their findings for both technical and non-technical audiences. Collaboration with data engineers, business analysts, and project managers is common, ensuring that data solutions align with organizational goals. This role offers opportunities to build expertise in specialized areas, such as machine learning or business intelligence, and can lead to career advancement in data science or analytics leadership positions.

What are the most commonly searched types of Python Data Analysis jobs in Montreal, QC? The most popular types of Python Data Analysis jobs in Montreal, QC are:
What job categories do people searching Python Data Analysis jobs in Montreal, QC look for? The top searched job categories for Python Data Analysis jobs in Montreal, QC are:
Senior Data Engineering Specialist (Hybrid)

Senior Data Engineering Specialist (Hybrid)

Morgan Stanley

Montreal, QC • On-site

Full-time

Posted 20 hours ago


Morgan Stanley rating

8.3

Company rating: 8.3 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

39th of 138 rated financial services


Job description

We're seeking someone to join our team as a Senior Data Engineering Specialist in the Enterprise Architecture & Modernization Fleet to build and evolve data platforms, pipelines, and analytics foundations that power firmwide architecture and modernization metrics. This position sits at the intersection of data engineering, analytics engineering, and decision-support analytics, with responsibility for multiple production-grade metrics products used across Technology. While the role requires strong technical execution, it also demands Director-level judgment, ownership, and stakeholder partnership.


In the Technology division, we leverage innovation to build the connections and capabilities that power our Firm, enabling our clients and colleagues to redefine markets and shape the future of our communities. This is a Lead Data & Analytics Engineering position at Director level, which is part of the job family responsible for providing specialist data analysis and expertise that drive
decision-making and business insights as well as crafting data pipelines, implementing data models, and optimizing data processes for improved data accuracy and accessibility, including applying machine learning and AI-based techniques

Since 1935, Morgan Stanley is known as a global leader in financial services, always evolving and innovating to better serve our clients and our communities in more than 40 countries around the world.
Interested in joining a team that's eager to create, innovate and make an impact on the world? Read on...

What you'll do in the role:


Provide senior technical leadership and delivery ownership across the Metrics & KPIs squad, supporting multiple enterprise data products spanning architecture metrics, modernization scoring, vendor software analysis, AI adoption, and technology spend transparency.
Lead the design, development, and operation of end-to-end data pipelines that ingest, validate, transform, and publish datasets from diverse firmwide sources into Snowflake-based analytical data stores.
Design and maintain semantic data models and KPI definitions that enable consistent, trusted measurement across executive dashboards, ad-hoc analytics, and downstream consumption. Ensure metrics are explainable, reconcilable, and aligned to Technology Strategy objectives.
Build and evolve analytics and insight layers using Power BI and Streamlit, delivering executive-ready dashboards and interactive analytical experiences that emphasize trends, drivers, and decision implications rather than static reporting.
Support delivery and integration across the Metrics & KPIs product portfolio, including technology and architecture telemetry ingestion and platform metrics; system and architectural complexity scoring; technology fitness and modernization progress measurement; vendor software technical rating and AI sensitivity analysis; firmwide AI cost, usage, and engagement analytics; and product portfolio, decommissioning, and software spend analytics.
Partner closely with Enterprise Architects, Modernization leads, Risk and Resilience teams, and Technology Strategy stakeholders to understand evolving measurement needs and translate them into durable, scalable data solutions.
Advance the squad's roadmap toward predictive and forward-looking analytics, identifying opportunities where forecasting, trend modeling, simulation, or anomaly detection can materially improve planning, prioritization, and governance.
Contribute to engineering standards, development practices, technical documentation, and mentorship within the squad through code reviews, design guidance, and hands-on leadership.

What you'll bring to the role:


6+ years of experience as a hands-on data engineering or analytics engineering practitioner, with sustained ownership of production-grade, enterprise-scale data platforms used by senior stakeholders.
Demonstrated expertise in advanced SQL and analytical data modeling, including the design and governance of metric-centric and semantic models that support consistent KPIs across multiple consumption patterns.
Significant experience designing, building, and operating data solutions on Snowflake, including ELT-based architectures, performance optimization, and cost-aware design for large analytical workloads.
Strong proficiency in Python for data engineering and analytics use cases, including pipeline development, data validation, orchestration logic, and analytical workflows.
Proven ability to design and operate end-to-end data pipelines encompassing ingestion, transformation, validation, metadata enrichment, lineage, and operational monitoring in regulated, reliability-sensitive environments.
Experience establishing and enforcing data quality standards and engineering best practices that materially increase trust in metrics used for executive decision-making.
Experienced in building strong stakeholder partnerships, translating leadership questions into actionable data products and outcomes, and independently prioritizing and leading delivery within a global team using sound technical judgment.
Exposure to building analytics and decision-support applications using AI, Power BI and/or Streamlit, with a focus on insight-driven narratives rather than static reporting.
Preferred exposure to, or strong aptitude for, data science and predictive analytics, such as forecasting, trend modeling, anomaly detection, simulation, or experimentation-particularly when applied to technology or platform telemetry.

At Morgan Stanley Montreal, we support the Firm's global businesses and infrastructure with cutting edge technology and innovation. The multi-faceted and highly technical Montreal team plays a critical role in building and maintaining our leading technology platform, including electronic trading, algorithm trading, cloud engineering, infrastructure, cybersecurity and AI/ML. Morgan Stanley has been rooted in the Montreal community since 2008 and is considered a leading employer among the area's highly skilled technology talent. There's ample opportunity to move across the businesses for those who show passion and grit in their work.


Morgan Stanley is an equal opportunities employer. We work to provide a supportive and inclusive environment where all individuals can maximize their full potential.

All our positions are located in Montreal, Quebec. We offer a hybrid work environment, combining remote work and attendance in the office.


Knowledge of French and English is required.


Build a career with impact. Visit morganstanley.com for more information.

WHAT YOU CAN EXPECT FROM MORGAN STANLEY:

At Morgan Stanley, we raise, manage and allocate capital for our clients - helping them reach their goals. We do it in a way that's differentiated - and we've done that for 90 years. Our values - putting clients first, doing the right thing, leading with exceptional ideas, committing to diversity and inclusion, and giving back - aren't just beliefs, they guide the decisions we make every day to do what's best for our clients, communities and more than 80,000 employees in 1,200 offices across 42 countries. At Morgan Stanley, you'll find an opportunity to work alongside the best and the brightest, in an environment where you are supported and empowered. Our teams are relentless collaborators and creative thinkers, fueled by their diverse backgrounds and experiences. We are proud to support our employees and their families at every point along their work-life journey, offering some of the most attractive and comprehensive employee benefits and perks in the industry. There's also ample opportunity to move about the business for those who show passion and grit in their work.

To learn more about our offices across the globe, please copy and paste https://www.morganstanley.com/about-us/global-offices into your browser.

Morgan Stanley is an equal opportunity employer committed to building and maintaining a workforce that is diverse in experience and background. Our recruiting efforts reflect our strong commitment to a culture of inclusion, where individuals are hired, developed, and advanced based on their skills and talents.

Our workforce reflects a broad cross-section of the global communities in which we operate, bringing a variety of backgrounds, talents, perspectives, and experiences.

For more information, please visit: https://www.morganstanley.com/people-opportunities/eeo.


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