Senior Associate, Data Scientist - Recommendation & Personalization Systems
for section headings. Use - for any list of duties/requirements/benefits. Use
for prose.
We must not repeat job title as heading. No Job ID.
We must include sections only when posting has real specific content. So we need sections: About the role (maybe from first paragraph?), Responsibilities (the bullet list after "In this role, you will:"), Requirements (maybe basic qualifications?), Qualifications (maybe preferred qualifications?), Skills (maybe technical stack?), Benefits (benefits description), Pay (salary ranges), Schedule (maybe not present; posting does not mention schedule specifics, so we should not include Schedule section). Also maybe "Team Description" could be part of About the role.
We need to preserve all substantive information, not invent or summarize away detail. So we need to include details like technologies: Python, Conda, AWS, H2O, Spark, etc. Also mention "Partner with a cross-functional team..." etc.
We need to avoid filler like "commensurate with experience". Not present.
We need to remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we need to cut out the paragraphs about accommodation, equal opportunity, etc. Also the part about "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." That's substantive? It's about visa sponsorship; maybe keep? It's not boilerplate but it's a detail. Might keep under Requirements or Qualifications? It's about eligibility. Could be part of Requirements. But it's not a typical qualification; it's about sponsorship. Might keep as a note.
Also "This role is also eligible to earn performance based incentive compensation..." that's substantive about compensation; could go under Benefits or Pay? Probably Benefits.
Also "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits..." that's Benefits.
Also "Learn more at the Capital One Careers website." that's generic; maybe drop as boilerplate? It's a link to benefits; but it's generic. Might drop.
Also "Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." That's about benefits eligibility; could be part of Benefits.
Also "This role is expected to accept applications for a minimum of 5 business days. No agencies please." That's application instruction; drop.
Also EEO statements etc drop.
Also "Capital One promotes a drug-free workplace." drop.
Also "Capital One will consider for employment qualified applicants with a criminal history..." drop.
Also accommodation contact drop.
Also technical support email drop.
Also disclaimer about third-party products drop.
Also note about Canada/UK/Philippines drop.
Thus we keep core content.
Now structure:
About the role
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 Data Scientist 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 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.
Maybe also include Team Description: "Join an elite Applied AI team within AI Foundations, operating at the intersection of deep research and massive real-world impact. We are pioneering the next generation of personalized customer experiences across Capital One's web and mobile applications, leveraging our high-scale ML models. Our core mission involves architecting and deploying cutting-edge personalized recommendation engines. This is powered by original research into homegrown Foundation Models, advanced Reinforcement Learning techniques, and a state-of-the-art scalable architecture built for billions of interactions. Our research agenda is at the forefront of the field, actively focusing on areas such as Causal Inference, Transformer-based architectures, and sophisticated Recommender Systems."
We could incorporate that into About the role or separate section? The instruction says use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can put team description under About the role.
Now Responsibilities: bullet list from "In this role, you will:" includes:
- Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love
- Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data
- Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation
- Flex your interpersonal skills to translate the complexity of your work into tangible business goals
We'll put each as - .
Now Requirements: maybe Basic Qualifications? The heading "Requirements" could be used for basic qualifications. We'll list them.
Basic Qualifications:
- Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
- A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
- 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
We could also include visa sponsorship note? Might be under Requirements as well.
Now Qualifications: maybe Preferred Qualifications.
Preferred Qualifications:
- Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
- Experience working with AWS
- At least 2 years of experience in Python, Scala, or R
- At least 2 years of experience with machine learning
- At least 2 years of experience with SQL
Now Skills: maybe the technical stack mentioned earlier? Could be under Skills: Python, Conda, AWS, H2O, Spark, etc. But we already listed some under Preferred Qualifications. However we can still have a Skills section summarizing technical skills: Python, Conda, AWS, H2O, Spark, etc. But we must not duplicate content? The instruction says preserve ALL substantive information; do NOT invent or summarize away detail. Duplication is okay if it's present in posting? Might be okay but better to avoid redundancy. We could put the stack under Skills, and keep Preferred Qualifications separate (they overlap). But we need to decide.
Maybe we treat Skills as the technical stack: Python, Conda, AWS, H2O, Spark, etc. And keep Preferred Qualifications as education/experience.
Now Benefits: include:
- Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.
- Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.
- This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.
We could also mention visa sponsorship? Might be under Benefits? Probably not.
Now Pay: include salary ranges per location:
- McLean, VA: $135,600 - $154,800 for Sr Assoc, Data Science
- New York, NY: $148,000 - $168,900 for Sr Assoc, Data Science
- San Jose, CA: $148,000 - $168,900 for Sr Assoc, Data Science
- Note: Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
We should keep that.
Now Schedule: not present, so omit.
Now we need to output only HTML fragment, no markdown fences.
Let's craft.
We need to ensure we use
for each section heading.
We'll produce:
About the role
... (combined description)
Responsibilities
- ...
...
Requirements
- ...
...
Qualifications
- ...
...
Skills
- ...
...
Benefits
- ...
...
Pay
- ...
...
We need to ensure we don't include empty sections.
Now let's write the content precisely.
About the role paragraph: combine first paragraph and team description.
First paragraph: "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 Data Scientist 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 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."
Team description: "Join an elite Applied AI team within AI Foundations, operating at the intersection of deep research and massive real-world impact. We are pioneering the next generation of personalized customer experiences across Capital One's web and mobile applications, leveraging our high-scale ML models. Our core mission involves architecting and deploying cutting-edge personalized recommendation engines. This is powered by original research into homegrown Foundation Models, advanced Reinforcement Learning techniques, and a state-of-the-art scalable architecture built for billions of interactions. Our research agenda is at the forefront of the field, actively focusing on areas such as Causal Inference, Transformer-based architectures, and sophisticated Recommender Systems."
We can combine into one or two
? The instruction says use
for prose. Could have multiple
under same heading. We'll do two
under About the role.
Now Responsibilities list as above.
Now Requirements list: Basic Qualifications.
We need to capture the nuance: "Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:" then two bullet points.
We'll make each bullet as
- containing the full text.
Thus:
- Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date: A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics
for prose. We must not repeat job title as heading. No Job ID. We must include sections only when posting has real specific content. So we need sections: About the role (maybe from first paragraph?), Responsibilities (the bullet list after "In this role, you will:"), Requirements (maybe basic qualifications?), Qualifications (maybe preferred qualifications?), Skills (maybe technical stack?), Benefits (benefits description), Pay (salary ranges), Schedule (maybe not present; posting does not mention schedule specifics, so we should not include Schedule section). Also maybe "Team Description" could be part of About the role. We need to preserve all substantive information, not invent or summarize away detail. So we need to include details like technologies: Python, Conda, AWS, H2O, Spark, etc. Also mention "Partner with a cross-functional team..." etc. We need to avoid filler like "commensurate with experience". Not present. We need to remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we need to cut out the paragraphs about accommodation, equal opportunity, etc. Also the part about "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." That's substantive? It's about visa sponsorship; maybe keep? It's not boilerplate but it's a detail. Might keep under Requirements or Qualifications? It's about eligibility. Could be part of Requirements. But it's not a typical qualification; it's about sponsorship. Might keep as a note. Also "This role is also eligible to earn performance based incentive compensation..." that's substantive about compensation; could go under Benefits or Pay? Probably Benefits. Also "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits..." that's Benefits. Also "Learn more at the Capital One Careers website." that's generic; maybe drop as boilerplate? It's a link to benefits; but it's generic. Might drop. Also "Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." That's about benefits eligibility; could be part of Benefits. Also "This role is expected to accept applications for a minimum of 5 business days. No agencies please." That's application instruction; drop. Also EEO statements etc drop. Also "Capital One promotes a drug-free workplace." drop. Also "Capital One will consider for employment qualified applicants with a criminal history..." drop. Also accommodation contact drop. Also technical support email drop. Also disclaimer about third-party products drop. Also note about Canada/UK/Philippines drop. Thus we keep core content. Now structure:
About the role
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 Data Scientist 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 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.
Maybe also include Team Description: "Join an elite Applied AI team within AI Foundations, operating at the intersection of deep research and massive real-world impact. We are pioneering the next generation of personalized customer experiences across Capital One's web and mobile applications, leveraging our high-scale ML models. Our core mission involves architecting and deploying cutting-edge personalized recommendation engines. This is powered by original research into homegrown Foundation Models, advanced Reinforcement Learning techniques, and a state-of-the-art scalable architecture built for billions of interactions. Our research agenda is at the forefront of the field, actively focusing on areas such as Causal Inference, Transformer-based architectures, and sophisticated Recommender Systems." We could incorporate that into About the role or separate section? The instruction says use headings for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. So we can put team description under About the role. Now Responsibilities: bullet list from "In this role, you will:" includes: - Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love - Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data - Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation - Flex your interpersonal skills to translate the complexity of your work into tangible business goals We'll put each as for each section heading.
We'll produce:
About the role
... (combined description)
Responsibilities
- ... ...
Requirements
- ... ...
Qualifications
- ... ...
Skills
- ... ...
Benefits
- ... ...
Pay
- ... ...
or two
? The instruction says use
for prose. Could have multiple
under same heading. We'll do two
under About the role. Now Responsibilities list as above. Now Requirements list: Basic Qualifications. We need to capture the nuance: "Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:" then two bullet points. We'll make each bullet as