aipythonsqlexceldata visualizationfinancial analysistime series analysisleveraged financecredit analysis
Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Мало
65к-90к CAD/год
98к CAD120к CADмедиана140к CAD
По похожим ролям (49) ~ 120к CAD/год
На СНГ рынке: $2.8к/мес ($2.2к - $2.9к)
75
Хорошая вакансия
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Обязанности чётко описаны и сочетают количественные исследования с кредитным анализом, однако четыре дня в офисе и строгие правила по личным инвестициям ограничивают гибкость.
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Ниже рынкаМного офисаОграничения инвестицийАктуальные инструментыРост ответственности
Оценка от Hirify AI
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Senior Analyst, Private Corporate Credit (Financial Data and Leveraged Finance): Analyzing financial and economic data, developing quantitative tools, and supporting credit surveillance and ratings for highly leveraged middle-market companies with an accent on financial modeling, time-series analysis, and credit fundamentals. Focus on building analytical structures in Excel, Python, and SQL, preparing rating committee materials, and translating complex market data into actionable credit insights.
Location: Toronto, Canada; hybrid work with four days in-office each week in most locations.
Base salary: CAD 65,000–90,000 annually; 15% annual incentive target.
Company
Morningstar DBRS provides credit research, ratings, and market insights for investment and lending decisions.
What you will do
Source, validate, organize, and analyze financial and economic data for leveraged finance research and credit analysis.
Design and maintain data structures and analytical tools using Excel, Python, SQL, and other platforms.
Create charts, tables, and data visualizations for research and credit publications.
Apply time-series and cross-sectional quantitative methods to identify trends across financial markets and leveraged finance.
Support credit analysis and surveillance of small to medium-sized, highly leveraged companies by reviewing financial statements and credit fundamentals.
Prepare rating committee materials, develop credit recommendations, participate in committee discussions, and maintain relationships with lenders, investors, and bankers.
Requirements
Two to four years of relevant experience in financial data analytics, quantitative research, corporate credit analysis, leveraged finance, corporate lending, or a related analytical discipline.
Bachelor’s degree in finance, economics, business, data analytics, or a related field.
Strong financial and quantitative analytical skills, including experience with financial statements, economic data, and large financial datasets.
Experience with time-series and cross-sectional data analysis and an interest in quantitative methods applied to financial markets and credit research.
Advanced Microsoft Excel proficiency and strong working knowledge of Python and SQL for financial data analysis, manipulation, and reporting.
Strong written and verbal communication skills, attention to detail, a proactive collaborative approach, and the ability to manage multiple priorities in a fast-paced environment.
Nice to have
Progress toward the CFA designation.
Familiarity with data visualization tools such as Tableau.
Experience using AI platforms such as Microsoft Copilot or Claude for research, data analysis, or workflow efficiency.
Culture & Benefits
Hybrid work environment with regular in-person collaboration, typically four office days per week.
Tools and resources for meaningful collaboration with global colleagues.
Additional benefits supporting flexibility as needs change.
Personal and related investments must be disclosed to Compliance and comply with the Code of Ethics; applicable employee accounts may need to be held with an approved broker.
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