Senior Quantitative Analyst - Global Finance
- list.
List items:
- Partner with the various lines of business to develop and enhance Capital Markets modeling and analytical framework, such as derivatives models and fixed income models.
- Work across Capital One entities to create novel analytical solutions to challenging business problems.
- Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies.
- Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data.
- Identify opportunities to apply quantitative methods or machine learning to improve business performance.
- Apply deep expertise in mathematics, statistical and machine learning methods to generate critical insights and decision frameworks for our business and customers.
- Providing technical guidance to business leadership.
- Communicate technical subject matter clearly and concisely to individuals from various backgrounds.
- Understand and navigate Risk Management Software to enable business analysis.
- Expertise in quantitative analysis is central to our success in all markets.
- Our modelers thrive in a culture of mutual respect, excellence and innovation.
But some of these are not responsibilities but maybe statements. However we can include them as list items.
Then "Successful candidates would possess:" list:
- Deep understanding of quantitative modeling in relation to finance, capital markets, derivatives and investment portfolio modeling principles.
- Extensive experience in Python or other object-oriented language.
- Ability to clearly communicate modeling results to a wide range of audiences.
- Drive to develop and maintain high quality and transparent model documentation.
- Strong written and verbal communication skills.
- Strong presentation skills.
- Ability to fully own the model development process: from conceptualization through data exploration, model selection, validation, deployment, business user training, and monitoring.
Then "Basic Qualifications:" list:
- Currently has, or is in the process of obtaining one of the following with an exception that the required degree will be obtained on or before the scheduled start date: A Master’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 1 year of experience in quantitative analytics
- At least 1 year of experience in each of the following skills through education or experience:
- Statistical or econometric modeling
- Linear and logistic regression
- Programming in R, Python or SQL
- Presenting statistical concepts and research results to non-statistical audience
- At least 1 year of experience in at least 3 of the following skills:
- Survival analysis modeling
- Time-series analysis
- Panel data (longitudinal data or cross-sectional time-series data) analysis
- Cross-sectional data analysis
- Machine learning
- Analysis and management of large datasets (>1M records)
Then "Preferred Qualifications:" list:
- 2 years of experience with Python, R or other statistical analyst software
- Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.
Then salary info: "The minimum and maximum full-time annual salaries for this role are listed below, by location." Then location: McLean, VA: $135,600 - $154,800 for Sr Assoc,Quantitative Analysis. Also note other details about part-time, incentives, etc. We need to include Pay section only if posting actually states them. Yes they state salary range for McLean, VA. Also mention performance based incentive compensation. Also mention benefits: "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being." Also mention eligibility varies etc. But we should not include boilerplate like eligibility varies based on full or part-time status etc? That's still substantive? Might be considered boilerplate but it's about benefits eligibility. The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Benefits info is not boilerplate; it's substantive. However we should avoid generic statements like "Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." That's still somewhat generic but it's about benefits eligibility. Might keep but could be considered boilerplate. Safer to include a Benefits section with the statement about comprehensive benefits and maybe mention health, financial, other benefits. The rest about eligibility maybe drop as it's generic.
Also mention "This role is expected to accept applications for a minimum of 5 business days. No agencies please." That's application instruction; should be removed.
Also EEO etc remove.
Also mention about accommodation contact etc - that's application instruction/accommodation; maybe remove as it's not core job description? Might be considered boilerplate but it's about accommodation. The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Accommodation contact is application instruction? Probably yes, remove.
Also technical support email etc remove.
Also disclaimer about third-party products etc remove.
Also note about Canada/UK/Philippines entity note - that's maybe not needed; could be considered boilerplate? It's about location specifics; but it's not core job description. Might remove.
Thus sections: About the role? Could have an introductory paragraph(s). Could have a section "About the role" or "Overview". The instruction: use h3 for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We need to decide which headings to use based on content.
We have:
- Overview/intro: maybe "About the role" or "Overview". We'll use
About the role
and put the introductory paragraphs. - Responsibilities:Responsibilities
with ul list. - Skills: maybe combine with Responsibilities? But we have separate "Successful candidates would possess:" which is more like Skills/Qualifications. Could useSkills
for that list. - Qualifications: we have Basic Qualifications and Preferred Qualifications. Could combine intoQualifications
with sublists? Or separate Basic and Preferred? The instruction says prefer a few substantive sections over many thin ones. So we could have one Qualifications section containing both basic and preferred as sublists. - Benefits:Benefits
with statement about comprehensive benefits. - Pay:Pay
with salary range and incentive info. - Schedule: not present; omit. We must not include sections with filler like "commensurate with experience". We have actual salary range. Now produce HTML fragment. We need to ensure we usefor headings,
- for lists,
for prose. We must not include markdown fences. Let's craft. First, introductory prose: combine the first paragraphs up to "This position offers a unique opportunity..." maybe also the sentence about CMA organization journey. We'll put in
. Let's extract: "At Capital One data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making. As a Quantitative Analyst at Capital One, you’ll be part of a team that’s leading the next wave of disruption at a whole new scale, using the latest in cloud computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives. This position offers a unique opportunity to be a part of the modeling and quantitative analytics team in the dynamic Capital Markets & Analytics (CMA) organization at Capital One. The CMA organization has been on a technology journey seeking to find ways to leverage technology to drive deeper market insights, manage financial risks and make the complex simple. We are looking for candidates to help in our journey with modeling, analytical and model implementation skills." That's good. Now Responsibilities list: we need to capture the bullet points after "Responsibilities and Skills:" up to before "Successful candidates would possess:" Actually the text: "Responsibilities and Skills: Partner with the various lines of business to develop and enhance Capital Markets modeling and analytical framework, such as derivatives models and fixed income models. Work across Capital One entities to create novel analytical solutions to challenging business problems. Identify opportunities to apply quantitative methods and automation solutions to improve business performance and process efficiencies. Collaborate in a cross-disciplinary team to build cloud-based solutions grounded in data. Identify opportunities to apply quantitative methods or machine learning to improve business performance. Apply deep expertise in mathematics, statistical and machine learning methods to generate critical insights and decision frameworks for our business and customers. Providing technical guidance to business leadership. Communicate technical subject matter clearly and concisely to individuals from various backgrounds. Understand and navigate Risk Management Software to enable business analysis. Expertise in quantitative analysis is central to our success in all markets. Our modelers thrive in a culture of mutual respect, excellence and innovation." We'll make each sentence a
- . Now Skills list: after "Successful candidates would possess:" we have list: - Deep understanding of quantitative modeling in relation to finance, capital markets, derivatives and investment portfolio modeling principles. - Extensive experience in Python or other object-oriented language. - Ability to clearly communicate modeling results to a wide range of audiences. - Drive to develop and maintain high quality and transparent model documentation. - Strong written and verbal communication skills. - Strong presentation skills. - Ability to fully own the model development process: from conceptualization through data exploration, model selection, validation, deployment, business user training, and monitoring. We'll put those as
- under Skills.
Now Qualifications: Basic Qualifications and Preferred Qualifications.
We need to preserve all substantive info. We'll combine into one Qualifications section with maybe two subheadings? But we cannot use headings inside? We could just have paragraphs and lists.
Better: Use
Qualifications
then havefor the basic qualifications description (the degree requirement) then
- for the specific skill requirements (the 1 year each, and at least 3 of list). Then another
for preferred qualifications: "2 years of experience with Python, R or other statistical analyst software" and "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." We must keep the nuance about degree: "Currently has, or is in the process of obtaining one of the following with an exception that the required degree will be obtained on or before the scheduled start date: A Master’s degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 1 year of experience in quantitative analytics". That's a bit long but we keep. Now Benefits:
Benefits
with"Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being." Could also add note about eligibility varies? Might drop as generic. Now Pay:
Pay
withcontaining salary range and incentive info. We need to include: "The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note
- for lists,