Senior Associate, Data Scientist - Applied AI

We need to output HTML fragment with sections: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Only include sections that have real specific content. We must not repeat job title as heading. No Job ID etc. Remove boilerplate. Preserve all substantive info. We need to parse the posting. Content: - Intro paragraph about data, startup, etc. Could be "About the role" maybe. - Team Description: Commercial Bank Applied AI team ... building enterprise-grade architectures using advanced techniques such as Multi-Agent Systems, Advanced RAG, Context Engineering, Tool-Calling Frameworks etc. The ideal candidate is deeply passionate about the practical applications of Generative AI and brings hands-on experience in machine learning and AI, gained through either professional industry work or rigorous academic research. - In this role, you will: bullet list (Partner with cross-functional team..., Leverage a broad stack..., Build Generative AI models..., Flex your interpersonal skills...) - The Ideal Candidate is: bullet list (Innovative..., Creative..., Technical..., Statistically-minded...) - Basic Qualifications: bullet 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 ... plus 2 years of experience performing data analytics; A Master's Degree in a quantitative field ... or an MBA with a quantitative concentration) - Preferred Qualifications: bullet list (Master’s Degree in “STEM” field, or PhD in “STEM” field; 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; At least 1 year of experience in AI, Information Retrieval, Deep Learning, or NLP) - Capital One will consider sponsoring a new qualified applicant for employment authorization for this position. - Salary info: The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked. McLean, VA: $135,600 - $154,800 for Sr Assoc, Data Science New York, NY: $148,000 - $168,900 for Sr Assoc, 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. 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. - Benefits: 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. - Additional info: This role is expected to accept applications for a minimum of 5 business days. No agencies please. EEO etc. We need to remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we should remove the EEO statements, accommodation contact, etc. Also remove "This role is expected to accept applications for a minimum of 5 business days. No agencies please." That's application instruction? Probably remove. Also remove the accommodation contact lines. Also remove the lines about Capital One does not provide third-party products etc. Also remove the lines about Capital One Financial made up of several entities etc. We need to preserve all substantive information: So we keep the intro paragraphs, team description, responsibilities, ideal candidate, basic qualifications, preferred qualifications, sponsorship note, pay, benefits. Also maybe note about sponsorship. We need to structure sections: Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We need to decide which sections to include. We have content for: - About the role: could be the introductory paragraph(s) describing the role, mission, team description. Could combine intro and team description. - Responsibilities: the bullet list under "In this role, you will:". - Requirements: maybe Basic Qualifications? Or "Requirements" could be basic qualifications. The spec says use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we have both Requirements and Qualifications separate. Likely Requirements = basic qualifications (must-have). Qualifications = preferred qualifications (nice-to-have). Skills could be the ideal candidate traits (Innovative, Creative, Technical, Statistically-minded) maybe also tech stack? But we already have tech stack in responsibilities. Could put skills under Skills section: maybe list of technologies: Python, PyTorch, LangChain, AWS, Spark, Vector Databases. Also mention open-source languages, cloud computing platforms. But we need to avoid duplication. Let's think. We have: - Ideal Candidate traits: Innovative, Creative, Technical, Statistically-minded. Could go under Skills. - Tech stack: Python, PyTorch, LangChain, AWS, Spark, Vector Databases. Could also go under Skills. - Experience requirements: 2 years experience performing data analytics (for Bachelor's) etc. That's more qualifications. Thus we can allocate: About the role: intro paragraph + team description. Responsibilities: bullet list of duties. Requirements: Basic Qualifications (bullet list). Qualifications: Preferred Qualifications (bullet list). Skills: Ideal Candidate traits + tech stack (maybe combine). Could also include "Statistically-minded" etc. Benefits: paragraph about benefits. Pay: salary ranges and incentive info. Schedule: Not provided. No schedule info. So we should NOT include Schedule section because no specific content. The instruction: "include a section ONLY when the posting has real, specific content for it — never emit a heading followed by filler/placeholder text". So we omit Schedule. Also we might omit "Requirements" if we think it's covered by Qualifications? But we have both basic and preferred; we can map Requirements to basic qualifications, Qualifications to preferred qualifications. Now we need to output HTML fragment only, no /, no markdown fences. We'll produce something like:

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. Team Description The Commercial Bank Applied AI team is at the forefront of embedding Generative AI directly into core business processes. We specialize in building enterprise-grade architectures using advanced techniques such as Multi-Agent Systems, Advanced RAG, Context Engineering, Tool-Calling Frameworks etc. The ideal candidate is deeply passionate about the practical applications of Generative AI and brings hands-on experience in machine learning and AI, gained through either professional industry work or rigorous academic research.

Responsibilities

• Partner with a cross-functional team of data scientists, machine learning engineers, and product managers to deliver Generative AI solutions customers love.
• Leverage a broad stack of technologies—Python, PyTorch, LangChain, AWS, Spark, and Vector Databases—to build Multi-Agent systems and advanced RAG pipelines over vast volumes of numeric and textual data.
• Build Generative AI models and pipelines through all phases of development, from context engineering through fine-tuning, evaluation, validation, and deployment.
• Flex your interpersonal skills to translate the complexity of your work into tangible business goals.

Requirements

• 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

Qualifications

• Master’s Degree in “STEM” field (Science, Technology, Engineering, or Mathematics), or PhD in “STEM” field (Science, Technology, Engineering, or Mathematics)
• 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
• At least 1 year of experience in AI, Information Retrieval, Deep Learning, or NLP

Skills

• Innovative: continually researches and evaluates emerging technologies, stays current on published state-of-the-art methods, technologies, and applications, seeks opportunities to apply them.
• Creative: thrives on bringing definition to big, undefined problems, loves asking questions and pushing hard to find answers, not afraid to share a new idea.
• Technical: comfortable with open-source languages, passionate about developing further, hands‑on experience developing data science solutions using open‑source tools and cloud computing platforms.
• Statistically‑minded: built models, validated them, backtested them, interprets confusion matrices or ROC curves, experienced with clustering, classification, sentiment analysis, time series, and deep learning.
• Technical stack proficiency: Python, PyTorch, LangChain, AWS, Spark, Vector Databases.

Benefits

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.

Pay

The minimum and maximum full‑time annual salaries for this role are: McLean, VA: $135,600 – $154,800 for Sr Assoc, Data Science; New York, NY: $148,000 – $168,900 for Sr Assoc, 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 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. Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

We need to ensure we didn't include any boilerplate like "Capital One is an equal opportunity employer..." etc. We removed those. Check for any leftover boilerplate: The paragraph about "Capital One will consider sponsoring a new qualified applicant for employment authorization for this position." we kept in Pay