Manager, Data Science - People Tech

We need to output HTML fragment with sections: headings

for sections like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title. Must not include Job ID etc. Must preserve all substantive info, not invent or summarize away detail. Remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning, duplicated lines, application instructions. Also remove "No agencies please", "Capital One is an equal opportunity employer..." etc. Also remove accommodation contact lines? Those are likely boilerplate. Also remove "Capital One does not provide..." etc. Also remove "Learn more at the Capital One Careers website." etc. We need to keep substantive info: description of company, team description, responsibilities (the bullet list after "In this role, you will:"), ideal candidate traits (list), basic qualifications, preferred qualifications, salary info (Pay), benefits mention (but we need actual benefits specifics? It says "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." That's vague; we might not include Benefits section because it's not specific. The rule: never create Benefits section unless posting actually states them. It states benefits exist but not specifics; maybe we can include a short paragraph? It says "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being." That's somewhat generic but still a statement about benefits. However rule: "never emit a heading followed by filler/placeholder text (e.g. 'commensurate with experience', 'not specified', 'N/A', 'varies', 'TBD')". This is not exactly placeholder but vague. Might be okay to include Benefits section with that sentence. But we need to decide. Pay: we have salary ranges per location. That's specific, so include Pay section. Schedule: not mentioned, so omit. About the role: we have introductory paragraph about data, startup, etc. Could be About the role. Responsibilities: the bullet list after "In this role, you will:" includes multiple items. Requirements: maybe combine Basic Qualifications and Preferred Qualifications? The rule: Use headings for Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide which to use. The posting has "Basic Qualifications:" and "Preferred Qualifications:" plus "The Ideal Candidate is:" list of traits. Could map: - About the role: intro paragraph. - Responsibilities: the bullet list after "In this role, you will:". - Requirements: maybe Basic Qualifications. - Qualifications: maybe Preferred Qualifications. - Skills: maybe the Ideal Candidate traits (skills/attributes). Or we could combine Ideal Candidate under Skills. We must not create thin sections. Let's see content volume. About the role: a few sentences. Responsibilities: bullet list of about 6 items. Requirements (Basic Qualifications): list of degree/experience combos plus some bullet points (at least 1 year experience leveraging open source programming languages..., at least 1 year experience working with machine learning..., at least 1 year experience utilizing relational databases). That's substantive. Qualifications (Preferred Qualifications): list of PhD in STEM, at least 4 years ML experience, at least 4 years AI modeling experience, at least 4 years experience in Python, Scala, or R, at least 4 years experience with SQL, Experience working with AWS. Skills: Ideal Candidate traits list: Experienced in taking models into production..., Customer first, Innovative, Creative, A leader, Technical, Influential, plus sub-bullets about expertise etc. That's substantive. Pay: salary ranges per location. Benefits: maybe include the generic benefits statement. Schedule: none. We must not include boilerplate like "Learn more at the Capital One Careers website." That's part of benefits statement; we could keep the benefits sentence but drop the "Learn more..." part. Also need to remove "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." That's substantive? It's about sponsorship; could be considered part of benefits or misc. Might keep as a short paragraph under Benefits or maybe under About the role? It's about visa sponsorship. Might be considered relevant. The instruction: remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. Sponsorship is not exactly those; it's a substantive detail about work authorization. Could keep. Also remove "This role is expected to accept applications for a minimum of 5 business days. No agencies please." That's application instructions; remove. Also remove EEO statements etc. Also remove "Capital One promotes a drug-free workplace." etc. Also remove "Capital One will consider for employment qualified applicants with a criminal history..." etc. Also remove accommodation contact lines. Also remove "For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com" etc. Also remove "Capital One does not provide, endorse nor guarantee..." etc. Also remove the note about Canada/UK/Philippines. Now construct HTML. We'll have sections:

About the role

... (intro paragraph plus maybe team description and sponsorship?)

We need to preserve all substantive information. Let's extract the substantive paragraphs: 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." Second paragraph: "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." Third: maybe sponsorship line: "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." We could combine these into About the role. Now Responsibilities: bullet list 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. Now Ideal Candidate traits: list after "The Ideal Candidate is:": - 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 treat these as Skills section. Now 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 Now Preferred Qualifications: - 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 Now 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 - 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. - 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 should keep that. Now Benefits: we have statement: "Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being." plus maybe sponsorship line? Actually sponsorship line we already placed in About the role. Benefits statement is vague but we could include as a short paragraph. We must not include "Learn more at the Capital One Careers website." So we strip that. Now ensure no duplicated lines. Now produce HTML. We'll wrap each section in

heading then content