Manager, Data Science - People Tech

We need to output HTML fragment with sections: About the role? The posting includes description. We need headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We have content: description of role, team description, responsibilities (In this role, you will: ...). Ideal Candidate (qualities). Basic Qualifications, Preferred Qualifications. Benefits mentioned: Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits. Also performance based incentive compensation. Also mention of sponsorship. Pay: salary ranges per location. Schedule: not mentioned (full-time implied). We can include Pay section with salary ranges. Benefits section with description. Possibly Schedule not present, so omit. We need to not repeat job title as heading. The job title is Data Scientist? Actually posting says Data Scientist at Capital One, but also mentions Mgr, Data Science in salary. We'll not add heading for title. We need to use

for section headings. Use

• for any list of duties/requirements/benefits. Use

  for prose. We must preserve all substantive information, not invent or summarize away detail. Remove boilerplate: cookie/navigation/legal/EEO etc. Remove duplicated lines, application instructions. So we need to strip out the EEO, accommodation, etc. Also remove "Capital One will consider sponsoring..." maybe keep as part of benefits? It's about employment authorization; could be considered a benefit? Might be considered part of "Benefits". But it's more about sponsorship. Could keep in a paragraph under Benefits or maybe a separate note. But we should keep substantive info: sponsorship mention. It's not boilerplate? It's about immigration sponsorship; it's substantive. Keep. Also remove "This role is expected to accept applications for a minimum of 5 business days. No agencies please." That's application instruction; remove. Also remove "Learn more at the Capital One Careers website." maybe part of benefits? It's a link; could be considered boilerplate? It's a reference; but it's about benefits. Might keep as part of benefits? It's generic; but it's referencing benefits page. Might be considered boilerplate; but it's about benefits. I'd keep it as part of benefits description. Also remove "Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level." That's benefits detail; keep? It's about benefits eligibility. Could keep in benefits. Also remove "Capital One promotes a drug-free workplace." etc. That's legal boilerplate; remove. Also remove "Capital One will consider for employment qualified applicants with a criminal history..." that's legal; remove. Also remove "If you have visited our website..." accommodation; remove? It's about accommodation; could be considered substantive? It's about providing accommodation; but it's more procedural. Might be considered boilerplate; but it's about accommodation request. Might keep? The instruction says remove EEO/equal-opportunity/scam-warning boilerplate. Accommodation request is related to EEO; likely remove. Also remove "For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com" remove. Also remove "Capital One does not provide, endorse nor guarantee..." remove. Also remove the paragraph about entities in Canada etc. That's legal; remove. Now we need to structure. Sections: - About the role: maybe a paragraph summarizing the role and team description. Could combine the initial paragraphs about data, team description. Use

  . - Responsibilities: list from "In this role, you will:" bullet points. - Requirements: maybe combine Basic Qualifications and Preferred Qualifications? But we have separate sections: Requirements and Qualifications. The instruction says use headings like Requirements, Qualifications, Skills. We need to decide what goes where. Typically Requirements = basic qualifications, Qualifications = preferred qualifications, Skills = technical skills list. We have Ideal Candidate traits (soft skills). Could put those under Skills? Or maybe under Qualities. But we have to follow instruction: use headings only when posting has real specific content. We have content for Ideal Candidate (traits). Could put under "Skills" or "Qualifications". Let's map: - Requirements: Basic Qualifications (education + experience). Use

  . - Qualifications: Preferred Qualifications (PhD, years experience, etc). Use
  . - Skills: Ideal Candidate traits (Customer first, Innovative, Creative, Leader, Technical, Influential) plus technical skills list (experience with LLMs, open source tools, cloud, etc). Could combine. But we also have technical skills mentioned in responsibilities: leverage stack, NLP expert, etc. Those could be under Skills as well. We need to avoid duplication. Let's extract lists. From responsibilities bullet points (after "In this role, you will:"): - Partner with a cross-functional team of data scientists, software engineers, machine learning engineers and product managers to deliver AI powered products that change how customers interact with their money. - Leverage a broad stack of technologies - Pytorch, AWS Ultraclusters, Hugging Face, LangChain, Lightning, VectorDBs, and more - to reveal the insights hidden within huge volumes of numeric and textual data. - Be the expert in Natural Language Processing (NLP) to harness the power of Large Language Models (LLMs), adapt and finetune them for customer facing applications and features. - Build machine learning and NLP models through all phases of development, from design through training, evaluation, and validation; partnering with engineering teams to operationalize them in scalable and resilient production systems that serve 80+ million customers. - Flex your interpersonal skills to translate the complexity of your work into tangible business goals. We can make each as
  • . Ideal Candidate traits list: - Experienced in taking models into production through the model risk compliance process - Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it’s about making the right decision for our customers. - Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them. - Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You’re not afraid to share a new idea. - A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond. - Technical. You’re comfortable with advanced ML and DL technologies including language models and are passionate about developing further. You have hands-on experience working with LLMs and solutions using open-source tools and cloud computing platforms. - Influential. You are passionate about AI/ML and can bring along a cross functional team in breakthrough innovations. You communicate clearly and effectively to share your findings with non-technical audiences. You are experienced in training language models or large computer vision models as well as have expertise in one or more key subdomains such as: training optimization, self-supervised learning, explainability, RLHF. You have an engineering mindset as shown by a track record of delivering models at scale both in training data and inference volumes. You have experience in delivering libraries, platforms, or solution level code to existing products. We could break these into separate
  • items. Basic Qualifications list: - 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 6 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 plus 4 years of experience performing data analytics - A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 1 year of experience performing data analytics - At least 1 year of experience leveraging open source programming languages for large scale data analysis - At least 1 year of experience working with machine learning - At least 1 year of experience utilizing relational databases Preferred Qualifications list: - PhD in “STEM” field (Science, Technology, Engineering, or Mathematics) - At least 4 years of machine learning experience - At least 4 years of AI modeling experience - At least 4 years of experience in Python, Scala, or R - At least 4 years of experience with SQL - Experience working with AWS Benefits: description: Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at the Capital One Careers website. 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. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. Pay: salary ranges per location: - McLean, VA: $197,300 - $225,100 for Mgr, Data Science - New York, NY: $215,200 - $245,600 for Mgr, Data Science - Plano, TX: $179,400 - $204,700 for Mgr, Data Science - 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. Schedule: not mentioned; omit. Now we need to output HTML fragment only. We'll structure:

    About the role

    ... (combined intro paragraphs about data, team description)

    Responsibilities

    • ...
    ...

    Requirements

    • ...
    ...

    Qualifications

    • ...
    ...

    Skills

    • ...
    ...

    Benefits

    ...

    Pay

    • ...
    ...
    We need to ensure we don't include empty sections. Now craft the About the role paragraph: combine 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." Then team description: "People Tech is a close-knit team of 480+ dedicated, talented and diverse individuals. Together, we're focused on delivering exceptional experiences and tech innovations for Capital One's associates and business partners. As a team, we deliver modern engineering capabilities, services, and platforms. We are the proud tech partner to the following enterprise lines of business: Brand, Corporate Development, Corporate Strategy, Experience Design, Enterprise Supplier Management, Global External Affairs, Human Resources, Legal, and Global Workplace Solutions." We can combine into one or two paragraphs. Use

    for each. Now Responsibilities list as