FP&A Consultant, Loyalty Programs
for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). Do NOT repeat the job title as a heading. The posting includes "About Us", "The Role", "A Day in the Life", "Requirements", "Benefits". We need to map to appropriate headings. Likely "About Us" -> About Us
. "The Role" maybe corresponds to "About the role". Use About the role
. "A Day in the Life" maybe not a standard heading; could be part of role description; but we can include as a subsection? The instruction: include a section ONLY when the posting has real, specific content for it. We could treat "A Day in the Life" as part of role description, maybe under About the role. But we could also make a separate heading like "A Day in the Life" but not in the list of allowed headings? The instruction says use for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). It gives examples but not exclusive; we can use other headings? Probably better to stick to those examples. So we can map content to those sections: About Us -> About Us (maybe not in list but okay). The Role -> About the role. Requirements -> Requirements. Benefits -> Benefits. Possibly Skills -> Skills (we have skills listed). Qualifications maybe not separate; we have qualifications within Requirements. Could combine.
We need to output only HTML fragment, no /. Use - for any list of duties/requirements/benefits, and
for prose.
We must preserve all substantive information, not invent or summarize away detail. Remove boilerplate etc.
We need to extract content:
About Us paragraph: "KYROS is the only actuarial firm solely focused on loyalty programs. We’re a small, boutique, fully remote consulting firm built by actuaries and technologists who wanted to rethink how actuarial work is done. We help your favorite frequent flyer program, hotel, bank or retail loyalty program measure and optimize the economic value that the program creates through a modern, highly technical combination of actuarial theory, machine learning, and big data technology. As a lean and growing team, we operate much more like a startup than a large consulting firm. We move quickly, expect a high level of execution, and rely on team members to take ownership of their work end to end. This is an environment for people who work efficiently, make sound decisions with incomplete information, and enjoy delivering high-quality work without layers of process or bureaucracy. We also leverage AI in service of human potential -- not to replace our people, but to amplify what they’re already great at. It’s freed our team up to spend more time on the work only a person can do: solving hard client problems, pushing into new territory, and building real relationships. If you’re comfortable working alongside AI as part of the job, you’ll fit right in here. Likewise, if you thrive on variety, enjoy coming to work not always knowing exactly how your day will unfold, and get energized by balancing multiple priorities in a fast-moving environment, this role is for you."
That's About Us.
The Role: "We’re looking for a highly motivated finance and analytics professional to help us manage and grow a portfolio of client relationships. This role is best suited for someone who has spent their career close to a loyalty, rewards, or points program — in FP&A, financial analysis, or a similar role inside an airline, hotel, retailer, bank, or other loyalty-driven business — and who is ready to bring that perspective to a wider range of clients. This is a place where you can make a real impact, as opposed to getting lost as one more cog in a big machine. You’ll act as the primary point of contact for a set of clients, partnering with our analysts and data scientists to scope and execute quantitative analyses rooted in machine learning. This includes estimating and forecasting loyalty program liability, customer lifetime value (CLV), and other key drivers of program economics. You don’t need to write the code yourself, and you don’t need to come from an actuarial or traditional consulting background — but you already understand how a loyalty program shows up on a company’s books and in its financial planning, and you can translate that fluency for our clients. Just as important as the domain fluency is the entrepreneurial mindset it takes to work here: clients bring us open-ended business problems with no existing solution, and you’ll need to be comfortable building a solution in the ambiguity rather than waiting for one to be handed to you. Even within our specialty, no two engagements look alike. Airline, hotel, retail, gaming, and ticketing loyalty programs all behave differently. If you’ve spent your career on the inside of one of these industries, this is a chance to use that experience across many programs instead of just one, while also being at the forefront of innovation that will take loyalty program analytics to the next level."
A Day in the Life: bullet-like sentences but we can put as prose or list. It says: "No two days look exactly the same, but here’s what the work typically looks like: You’re the first call for a set of assigned clients, fielding quick ad hoc questions one moment and steering a multi-week project the next You work with analysts and data scientists to translate a client’s business problem into a structured quantitative analysis, then build and manage the project plan to keep it on track You dig into the outputs of predictive models to sanity-check the results and understand what’s really driving them, not just what the model produced You synthesize those results into a clear narrative: building the slides, the talk track, and the recommendation that helps a non-technical client make a real business decision You present to clients directly, fielding questions in real time and adjusting the story based on what matters most to them In between, there’s always ad hoc work, from a client question that needs a quick turnaround to a problem nobody at KYROS (or elsewhere) has solved before You stay connected through a steady cadence of team standups, a structure that keeps our fully remote team organized and workloads manageable There’s also real opportunity to shape how we work: to improve our client deliverables, contribute to internal tools like our KPI validation platform, and help define what a great client engagement looks like as we grow."
We could format as
- each sentence.
Requirements: list of bullet points: "Basic qualifications Years of Experience: At least 5 years of professional experience, ideally in FP&A, financial analysis, or a related finance/strategy role Education: Bachelor’s degree in math, statistics, economics, finance, or another quantitative field; candidates with strong analytical experience and a different academic background are also welcome to apply Industry Background: Direct experience with a loyalty, rewards, or points program — ideally at an airline, hotel, retailer, bank, or similar company — with a real understanding of how the program works and what drives its economics Analytical Rigor: Comfortable working with large transactional datasets, aggregating, structuring, and interpreting data to find the story inside it Project Management: Demonstrated experience owning relationships end-to-end, setting expectations, managing scope, and delivering results on tight timelines Business Sense: Ability to connect technical or financial analysis to a client’s business goals, understanding not just what a model says, but what it means and why it matters Skills: Advanced Excel skills (pivot tables, complex formulas, large dataset manipulation) and strong PowerPoint skills; a sharp sense for what makes a good chart, slide, or client story, including the ability to direct and critique AI-generated visuals and decks; experience with project management tools and data visualization software (e.g., Power BI) Modeling: Working understanding of predictive modeling concepts, sufficient to guide, question, and validate work performed by analysts and data scientists Communication: Ability to clearly distill complex, technical concepts into language non-technical audiences can understand and act on Other: Strong communicator, growth mindset, comfortable operating with ambiguity and little day-to-day guidance AI Fluency: Comfortable, and enthusiastic, about using AI tools as part of the daily workflow Bonus points if you have Prior experience in a client-facing consulting or advisory role Actuarial background or exam progress Prior experience in a small or startup-like consulting environment"
We need to split into sections: Requirements (maybe includes qualifications). Skills separate? The posting includes Skills within Requirements. But we can create a Skills section for the bullet list of skills (Excel, PowerPoint, etc.) and keep Requirements for experience, education, etc. However instruction: prefer a few substantive sections over many thin ones. Could combine Requirements and Skills into one Requirements section with sublists? But we must use
- for any list. Could have nested lists? Probably fine to have one
with items each being a category.
Simplify: Use Requirements section with - each bullet (Years of Experience, Education, Industry Background, Analytical Rigor, Project Management, Business Sense, Skills, Modeling, Communication, Other, AI Fluency, Bonus points). Within Skills item we can have a sublist? Might be okay to just include as text.
Benefits: list: Retirement Plan (401k with employer match), Qualified Small Employer Health Reimbursement Arrangement (QSEHRA), Discretionary PTO, Fully remote.
Pay and Schedule not present, so omit.
We must not include boilerplate like EEO etc. None present.
Now produce HTML:
About Us
...
About the role
...
Maybe also include "A Day in the Life" as part of About the role? Could add a separate heading "A Day in the Life" but not in examples. Safer to incorporate into About the role paragraph.
Thus we will have About Us, About the role, Requirements, Benefits.
Within About the role we can include the A Day in the Life content as prose.
Now craft HTML.
Need to escape any HTML special characters like &, <, >. The text includes em dashes — which is okay as is. Use plain text.
Let's construct.
About Us paragraph: copy exactly.
About the role: combine The Role and A Day in the Life.
We'll produce two paragraphs maybe.
Requirements: - each bullet.
We need to parse bullet list items:
- Years of Experience: At least 5 years of professional experience, ideally in FP&A, financial analysis, or a related finance/strategy role
- Education: Bachelor’s degree in math, statistics, economics, finance, or another quantitative field; candidates with strong analytical experience and a different academic background are also welcome to apply
- Industry Background: Direct experience with a loyalty, rewards, or points program — ideally at an airline, hotel, retailer, bank, or similar company — with a real understanding of how the program works and what drives its economics
- Analytical Rigor: Comfortable working with large transactional datasets, aggregating, structuring, and interpreting data to find the story inside it
- Project Management: Demonstrated experience owning relationships end-to-end, setting expectations, managing scope, and delivering results on tight timelines
- Business Sense: Ability to connect technical or financial analysis to a client’s business goals, understanding not just what a model says, but what it means and why it matters
- Skills: Advanced Excel skills (pivot tables, complex formulas, large dataset manipulation) and strong PowerPoint skills; a sharp sense for what makes a good chart, slide, or client story, including the ability to direct and critique AI-generated visuals and decks; experience with project management tools and data visualization software (e.g., Power BI)
- Modeling: Working understanding of predictive modeling concepts, sufficient to guide, question, and validate work performed by analysts and data scientists
- Communication: Ability to clearly distill complex, technical concepts into language non-technical audiences can understand and act on
- Other: Strong communicator, growth mindset, comfortable operating with ambiguity and little day-to-day guidance
- AI Fluency: Comfortable, and enthusiastic, about using AI tools as part of the daily workflow
- Bonus points if
- for any list of duties/requirements/benefits, and
for prose. We must preserve all substantive information, not invent or summarize away detail. Remove boilerplate etc. We need to extract content: About Us paragraph: "KYROS is the only actuarial firm solely focused on loyalty programs. We’re a small, boutique, fully remote consulting firm built by actuaries and technologists who wanted to rethink how actuarial work is done. We help your favorite frequent flyer program, hotel, bank or retail loyalty program measure and optimize the economic value that the program creates through a modern, highly technical combination of actuarial theory, machine learning, and big data technology. As a lean and growing team, we operate much more like a startup than a large consulting firm. We move quickly, expect a high level of execution, and rely on team members to take ownership of their work end to end. This is an environment for people who work efficiently, make sound decisions with incomplete information, and enjoy delivering high-quality work without layers of process or bureaucracy. We also leverage AI in service of human potential -- not to replace our people, but to amplify what they’re already great at. It’s freed our team up to spend more time on the work only a person can do: solving hard client problems, pushing into new territory, and building real relationships. If you’re comfortable working alongside AI as part of the job, you’ll fit right in here. Likewise, if you thrive on variety, enjoy coming to work not always knowing exactly how your day will unfold, and get energized by balancing multiple priorities in a fast-moving environment, this role is for you." That's About Us. The Role: "We’re looking for a highly motivated finance and analytics professional to help us manage and grow a portfolio of client relationships. This role is best suited for someone who has spent their career close to a loyalty, rewards, or points program — in FP&A, financial analysis, or a similar role inside an airline, hotel, retailer, bank, or other loyalty-driven business — and who is ready to bring that perspective to a wider range of clients. This is a place where you can make a real impact, as opposed to getting lost as one more cog in a big machine. You’ll act as the primary point of contact for a set of clients, partnering with our analysts and data scientists to scope and execute quantitative analyses rooted in machine learning. This includes estimating and forecasting loyalty program liability, customer lifetime value (CLV), and other key drivers of program economics. You don’t need to write the code yourself, and you don’t need to come from an actuarial or traditional consulting background — but you already understand how a loyalty program shows up on a company’s books and in its financial planning, and you can translate that fluency for our clients. Just as important as the domain fluency is the entrepreneurial mindset it takes to work here: clients bring us open-ended business problems with no existing solution, and you’ll need to be comfortable building a solution in the ambiguity rather than waiting for one to be handed to you. Even within our specialty, no two engagements look alike. Airline, hotel, retail, gaming, and ticketing loyalty programs all behave differently. If you’ve spent your career on the inside of one of these industries, this is a chance to use that experience across many programs instead of just one, while also being at the forefront of innovation that will take loyalty program analytics to the next level." A Day in the Life: bullet-like sentences but we can put as prose or list. It says: "No two days look exactly the same, but here’s what the work typically looks like: You’re the first call for a set of assigned clients, fielding quick ad hoc questions one moment and steering a multi-week project the next You work with analysts and data scientists to translate a client’s business problem into a structured quantitative analysis, then build and manage the project plan to keep it on track You dig into the outputs of predictive models to sanity-check the results and understand what’s really driving them, not just what the model produced You synthesize those results into a clear narrative: building the slides, the talk track, and the recommendation that helps a non-technical client make a real business decision You present to clients directly, fielding questions in real time and adjusting the story based on what matters most to them In between, there’s always ad hoc work, from a client question that needs a quick turnaround to a problem nobody at KYROS (or elsewhere) has solved before You stay connected through a steady cadence of team standups, a structure that keeps our fully remote team organized and workloads manageable There’s also real opportunity to shape how we work: to improve our client deliverables, contribute to internal tools like our KPI validation platform, and help define what a great client engagement looks like as we grow." We could format as
- each sentence.
Requirements: list of bullet points: "Basic qualifications Years of Experience: At least 5 years of professional experience, ideally in FP&A, financial analysis, or a related finance/strategy role Education: Bachelor’s degree in math, statistics, economics, finance, or another quantitative field; candidates with strong analytical experience and a different academic background are also welcome to apply Industry Background: Direct experience with a loyalty, rewards, or points program — ideally at an airline, hotel, retailer, bank, or similar company — with a real understanding of how the program works and what drives its economics Analytical Rigor: Comfortable working with large transactional datasets, aggregating, structuring, and interpreting data to find the story inside it Project Management: Demonstrated experience owning relationships end-to-end, setting expectations, managing scope, and delivering results on tight timelines Business Sense: Ability to connect technical or financial analysis to a client’s business goals, understanding not just what a model says, but what it means and why it matters Skills: Advanced Excel skills (pivot tables, complex formulas, large dataset manipulation) and strong PowerPoint skills; a sharp sense for what makes a good chart, slide, or client story, including the ability to direct and critique AI-generated visuals and decks; experience with project management tools and data visualization software (e.g., Power BI) Modeling: Working understanding of predictive modeling concepts, sufficient to guide, question, and validate work performed by analysts and data scientists Communication: Ability to clearly distill complex, technical concepts into language non-technical audiences can understand and act on Other: Strong communicator, growth mindset, comfortable operating with ambiguity and little day-to-day guidance AI Fluency: Comfortable, and enthusiastic, about using AI tools as part of the daily workflow Bonus points if you have Prior experience in a client-facing consulting or advisory role Actuarial background or exam progress Prior experience in a small or startup-like consulting environment"
We need to split into sections: Requirements (maybe includes qualifications). Skills separate? The posting includes Skills within Requirements. But we can create a Skills section for the bullet list of skills (Excel, PowerPoint, etc.) and keep Requirements for experience, education, etc. However instruction: prefer a few substantive sections over many thin ones. Could combine Requirements and Skills into one Requirements section with sublists? But we must use
- for any list. Could have nested lists? Probably fine to have one
- with items each being a category.
Simplify: Use Requirements section with
- each bullet (Years of Experience, Education, Industry Background, Analytical Rigor, Project Management, Business Sense, Skills, Modeling, Communication, Other, AI Fluency, Bonus points). Within Skills item we can have a sublist? Might be okay to just include as text.
Benefits: list: Retirement Plan (401k with employer match), Qualified Small Employer Health Reimbursement Arrangement (QSEHRA), Discretionary PTO, Fully remote.
Pay and Schedule not present, so omit.
We must not include boilerplate like EEO etc. None present.
Now produce HTML:
About Us
...
About the role
...
Maybe also include "A Day in the Life" as part of About the role? Could add a separate heading "A Day in the Life" but not in examples. Safer to incorporate into About the role paragraph. Thus we will have About Us, About the role, Requirements, Benefits. Within About the role we can include the A Day in the Life content as prose. Now craft HTML. Need to escape any HTML special characters like &, <, >. The text includes em dashes — which is okay as is. Use plain text. Let's construct. About Us paragraph: copy exactly. About the role: combine The Role and A Day in the Life. We'll produce two paragraphs maybe. Requirements:- each bullet. We need to parse bullet list items: - Years of Experience: At least 5 years of professional experience, ideally in FP&A, financial analysis, or a related finance/strategy role - Education: Bachelor’s degree in math, statistics, economics, finance, or another quantitative field; candidates with strong analytical experience and a different academic background are also welcome to apply - Industry Background: Direct experience with a loyalty, rewards, or points program — ideally at an airline, hotel, retailer, bank, or similar company — with a real understanding of how the program works and what drives its economics - Analytical Rigor: Comfortable working with large transactional datasets, aggregating, structuring, and interpreting data to find the story inside it - Project Management: Demonstrated experience owning relationships end-to-end, setting expectations, managing scope, and delivering results on tight timelines - Business Sense: Ability to connect technical or financial analysis to a client’s business goals, understanding not just what a model says, but what it means and why it matters - Skills: Advanced Excel skills (pivot tables, complex formulas, large dataset manipulation) and strong PowerPoint skills; a sharp sense for what makes a good chart, slide, or client story, including the ability to direct and critique AI-generated visuals and decks; experience with project management tools and data visualization software (e.g., Power BI) - Modeling: Working understanding of predictive modeling concepts, sufficient to guide, question, and validate work performed by analysts and data scientists - Communication: Ability to clearly distill complex, technical concepts into language non-technical audiences can understand and act on - Other: Strong communicator, growth mindset, comfortable operating with ambiguity and little day-to-day guidance - AI Fluency: Comfortable, and enthusiastic, about using AI tools as part of the daily workflow - Bonus points if
- each bullet (Years of Experience, Education, Industry Background, Analytical Rigor, Project Management, Business Sense, Skills, Modeling, Communication, Other, AI Fluency, Bonus points). Within Skills item we can have a sublist? Might be okay to just include as text.
Benefits: list: Retirement Plan (401k with employer match), Qualified Small Employer Health Reimbursement Arrangement (QSEHRA), Discretionary PTO, Fully remote.
Pay and Schedule not present, so omit.
We must not include boilerplate like EEO etc. None present.
Now produce HTML:
- for any list. Could have nested lists? Probably fine to have one
- each sentence.
Requirements: list of bullet points: "Basic qualifications Years of Experience: At least 5 years of professional experience, ideally in FP&A, financial analysis, or a related finance/strategy role Education: Bachelor’s degree in math, statistics, economics, finance, or another quantitative field; candidates with strong analytical experience and a different academic background are also welcome to apply Industry Background: Direct experience with a loyalty, rewards, or points program — ideally at an airline, hotel, retailer, bank, or similar company — with a real understanding of how the program works and what drives its economics Analytical Rigor: Comfortable working with large transactional datasets, aggregating, structuring, and interpreting data to find the story inside it Project Management: Demonstrated experience owning relationships end-to-end, setting expectations, managing scope, and delivering results on tight timelines Business Sense: Ability to connect technical or financial analysis to a client’s business goals, understanding not just what a model says, but what it means and why it matters Skills: Advanced Excel skills (pivot tables, complex formulas, large dataset manipulation) and strong PowerPoint skills; a sharp sense for what makes a good chart, slide, or client story, including the ability to direct and critique AI-generated visuals and decks; experience with project management tools and data visualization software (e.g., Power BI) Modeling: Working understanding of predictive modeling concepts, sufficient to guide, question, and validate work performed by analysts and data scientists Communication: Ability to clearly distill complex, technical concepts into language non-technical audiences can understand and act on Other: Strong communicator, growth mindset, comfortable operating with ambiguity and little day-to-day guidance AI Fluency: Comfortable, and enthusiastic, about using AI tools as part of the daily workflow Bonus points if you have Prior experience in a client-facing consulting or advisory role Actuarial background or exam progress Prior experience in a small or startup-like consulting environment"
We need to split into sections: Requirements (maybe includes qualifications). Skills separate? The posting includes Skills within Requirements. But we can create a Skills section for the bullet list of skills (Excel, PowerPoint, etc.) and keep Requirements for experience, education, etc. However instruction: prefer a few substantive sections over many thin ones. Could combine Requirements and Skills into one Requirements section with sublists? But we must use