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Added 11 mins ago
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- Full-time
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MCAP

Manager, Analytics & Process Innovation

Toronto, ON, Canada

Salary Range: $85,000 - $95,000 · Full-time

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Job details

Pay: Salary Range: $85,000 - $95,000
Job type: Full-time
Posting language: English
Posted: Oct 9, 2026

Original job description

Manager, Analytics & Process Innovation

MCAP at a Glance

Joining MCAP means you will be a part of our diverse workforce of highly talented individuals who are recognized for their expertise and success! At MCAP, your professional expertise, commitment to teamwork and passion for service excellence are recognized and rewarded with competitive total rewards offering, a career with continuous learning and development (formal & informal training), and exciting opportunities in a dynamic, entrepreneurial environment.

The Role

The role is responsible for identifying, designing, and implementing technology-driven solutions to improve Capital Markets processes, with a focus on process automation, quantitative analytics, data integration, reporting, and business intelligence. The role works with data from multiple sources to address complex business requirements, improve process efficiency and data quality, and support business decision-making.

The role requires a hands-on problem solver who can independently assess business requirements, interpret business strategy and logic, and develop practical technical and analytical solutions using SQL, Python, machine learning, and data integration technologies. The role is accountable for implementing and continuously improving approved solutions, working with the Director and business stakeholders, and may lead individual initiatives or workstreams. Knowledge of AI and LLM technologies is considered an asset.

Design, develop, and implement process automation solutions using SQL, Python, and other appropriate technologies to automate manual processes, improve efficiency, and reduce errors across hedging, sales activities, and day-to-day Capital Markets operations.
Apply quantitative analytics and mathematical or machine learning techniques to address business problems, integrate and interpret data from multiple sources, and develop data-driven insights and recommendations to support portfolio analysis and strategy optimization.
Develop and maintain reusable Business Intelligence solutions using Power BI, Tableau, or equivalent tools, including interactive dashboards and data visualizations, and apply technical judgment to improve how data and insights are presented for business decision-making.
Identify opportunities to improve reporting, data controls, and reconciliations across multiple systems and data sources. Independently investigate data differences, determine root causes, assess business impacts, recommend solutions, and work with teams such as Servicing and Data Engineering to resolve material data issues.
Apply business and technical judgment to complex or imperfect data, determining appropriate data rules, transformations, validation approaches, and programmatic solutions to address data limitations and meet business requirements.
Evaluate and apply emerging technologies, including Generative AI, LLMs, RAG, and AI agents, where appropriate to improve automation, analytics, knowledge management, and process efficiency within Capital Markets.

What You Bring To The Team

4+ years of relevant professional experience in quantitative analytics, business analytics, data analysis, software development, data integration, data engineering, or a related field
Hands-on experience developing and implementing automation solutions, including Python and SQL programming, data transformation, ETL/data integration, and working with data from multiple systems. Experience designing solutions to improve or automate manual or complex business processes is highly valued.
Practical experience applying quantitative analytics, mathematical, or machine learning techniques to financial, risk, or business problems, preferably within a bank or other financial services environment.
Strong understanding of analytical methodologies and their practical business application, with the ability to assess assumptions, limitations, drivers, and results, and communicate analytical findings and recommendations clearly to business stakeholders.
Experience independently translating business requirements into practical technical and analytical solutions, including interpreting business logic, assessing data limitations, and developing appropriate rules, transformations, validation approaches, and programmatic solutions.
Experience working with cross-functional stakeholders, including business, technology, data engineering, and servicing teams, to implement solutions and resolve data or technical issues.
Experience with Business Intelligence and data visualization tools such as Power BI, Tableau, or equivalent is an asset
Familiarity with Generative AI, LLMs, RAG, AI agents, or other emerging technologies and their potential business applications is an asset.
Requires practical knowledge of quantitative analytics, statistics, financial risk modeling, machine learning techniques such as logistic regression, decision trees, and XGBoost, SQL/Python development, and data integration, with the ability to apply this knowledge to complex business problems.
Requires knowledge of analytical methodologies and their practical application, including the ability to assess assumptions, limitations, and drivers, interpret results, and clearly explain machine learning models and their key drivers and limitations. Requires understanding of data structures, relationships, business logic, and data limitations across multiple systems and sources.
Requires sound knowledge of data structures, relationships, business logic, data integration, and data quality considerations across multiple systems and sources, with the ability to identify data limitations and determine appropriate technical or analytical approaches.
Requires practical knowledge of Capital Markets and financial services, including areas such as credit risk, securitization, investments, or related business processes.
Knowledge of emerging technologies and their practical business applications, including Generative AI, LLMs, RAG, and AI agents, is considered an asset.
Applies quantitative, statistical, and machine learning techniques to analyze financial and business problems, evaluate alternatives, and develop data-driven insights and recommendations.
Applies analytical and mathematical skills to independently identify patterns, assess alternatives, interpret results, and translate findings into practical business recommendations.
Designs and develops automation solutions using Python and SQL, including data integration, ETL processes, data transformations, and analytical applications across multiple systems.
Evaluates analytical methods, technologies, data sources, and tools to identify practical opportunities for process improvement, automation, and business analytics, and recommends appropriate approaches.
Translates business requirements into practical technical solutions, including developing business rules, data transformations, validation approaches, and programmatic solutions when data is incomplete or does not fully align with business requirements.
Integrates and analyzes data from multiple sources, independently investigates discrepancies and root causes, and applies appropriate technical and business judgment to determine practical solutions and support issue resolution.
Develops readable and maintainable code and technical solutions using Python, SQL, and other relevant technologies, applying appropriate development and data management practices.
Develops and interprets technical and analytical documentation and communicates technical concepts, analytical results, and recommendations clearly to internal stakeholders.
Works independently and collaborates effectively with business, technology, Data Engineering, Servicing, and other stakeholders to understand requirements, assess solution options, recommend practical approaches, and support implementation.

If this sounds like you and you are looking to be a part of one of Canada’s largest independent mortgage finance companies, then we want to hear from you!

Be A Part Of Something Great

MCAP is Canada’s largest independent Mortgage Finance company with over $150 billion in assets under management providing mortgage solutions for residential and commercial properties. For over 35 years, MCAP originates, trades, securitizes and services mortgages in offices across Canada. MCAP originates residential mortgages exclusively through the mortgage broker channel as we believe that a professional mortgage broker is a consumer's best option and MCAP actively promotes the services of mortgage brokers across the country. MCAP is also a leader in the Canadian residential construction lending market with over 25 years in the business. Our teams of dedicated professionals serve a variety of developer, construction and lender clients across Canada.

Position #: req2273

Employment Status: Permanent Full Time

Location: Toronto; Ontario

Number Of Openings: 1

Department: Capital Markets

Internal Job Title: Manager, Analytics & Process Innovation

Salary Range: $85,000 - $95,000

The above information in this description has been designed to indicate the general nature and level of work performed by employees in the position. It is not designated to contain a comprehensive inventory of all duties, responsibilities, and qualifications required of employees assigned to this job.

MCAP provides equal opportunities for all applicants and is committed to fostering an inclusive, accessible environment, where all employees feel valued, respected and supported throughout the recruitment and employment process. If you require accommodation, we will work with you to meet your needs.

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More about this job

Responsibilities

The role is responsible for designing and implementing technology-driven solutions to improve Capital Markets processes through automation, quantitative analytics, and data integration. It involves developing business intelligence tools and collaborating with cross-functional teams to resolve data issues and support strategic decision-making.

Requirements

Candidates must have 4+ years of professional experience in quantitative analytics, data engineering, or software development with hands-on proficiency in Python and SQL. A strong understanding of analytical methodologies, financial services, and the ability to translate complex business requirements into technical solutions is required.

Skills

SQL
Python
Machine learning
Data integration
Process automation
Quantitative analytics
Business intelligence
Power BI
Tableau
Data visualization
Financial risk modeling
ETL
Generative AI
LLMs
RAG
Capital markets

Benefits

Competitive total rewards offering
Continuous learning and development
Formal and informal training

Visa sponsorship

Not detected in the job text

Keywords

SQL
Python
Machine Learning
Data Integration
Process Automation
Quantitative Analytics
Business Intelligence
Power BI
Tableau
Data Visualization
Financial Risk Modeling
ETL
Generative AI
LLMs
RAG
Capital Markets
Credit Risk
Securitization
Data Engineering
XGBoost
Logistic Regression
Decision Trees
Data Quality
Reporting
Business Strategy
Portfolio Analysis
Strategy Optimization
Software Development
Data Analysis
AI Agents

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