Data Scientist III (US)

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 if posting has real specific content. We must preserve all substantive info, no boilerplate, no navigation, EEO, etc. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. We need to extract relevant content: Work Location, Hours, Pay Details, Line Of Business, Job Description (multiple paragraphs), Education & Experience, Preferred Skills, Customer Accountabilities, Shareholder Accountabilities, Employee/Team Accountabilities, Physical Requirements, Who We Are, Our Total Rewards Package, Additional Information (colleague development, training & onboarding, interview process, accommodation). Many of these may be considered boilerplate? The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The "Who We Are", "Our Total Rewards Package", "Additional Information" sections might be considered generic corporate fluff but they contain substantive info about benefits, development, etc. However we should only include sections when posting has real specific content for it. The posting includes Pay Details: $96,130 - $155,950 USD. So we can include Pay section with that range. Hours: 40 (presumably hours per week). So Schedule section could include "40 hours per week". Work Location: Mount Laurel, New Jersey, United States of America. Could be included maybe under About the role? But we have no specific heading for location; we could put location in a short

under About the role or as its own section? The instruction says use headings for section headings (About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can put location maybe under About the role. We need to decide what goes where. We have Job Description paragraphs: Department Summary, Job Description, Depth & Scope, etc. Those are responsibilities and qualifications. We can map: - About the role: maybe a brief summary: role is with US FCRM group, supports policies, etc. Could combine department summary and job description overview. - Responsibilities: list of duties: support team, provide strategic direction, oversee execution of reviews, etc. Could be bullet list. - Requirements: Education & Experience: Undergraduate degree or advanced technical degree preferred, Graduate's degree preferred with either progressive project work experience or 5+ year of relevant experience; higher degree education and research tenure can be counted. - Qualifications: maybe Preferred Skills list. - Skills: maybe technical skills: SQL, Python, etc. - Benefits: maybe from Total Rewards Package: base salary and variable compensation, health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, reward and recognition. But we need to ensure we only include if posting actually states them. It does state those in "Our Total Rewards Package". So we can include Benefits section with those items. - Pay: we have Pay Details: $96,130 - $155,950 USD. Also note that base pay may vary based on skills etc. We should include the range. - Schedule: Hours: 40 (presumably per week). Could also note domestic travel occasional, etc. But schedule section maybe just hours. We need to avoid filler like "commensurate with experience". The posting includes "The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs." That's not filler; it's substantive. We can include that in Pay section. We must not repeat the job title as a heading. The job title is Data Scientist III (implied). Not needed. We must not put Job ID/requisition numbers as headings. We must output only HTML fragment, no /, no markdown fences. Let's structure:

About the role

Work Location: Mount Laurel, New Jersey, United States of America. Hours: 40 hours per week. Line of Business: Analytics, Insights, & Artificial Intelligence. This role is within the US FCRM (Financial Crimes Risk Management) group of TD Bank, supporting a team that provides policies, standards, oversight, expert policy and regulatory guidance, and advice related to TD’s Data Governance Process. The Data Scientist III provides technical leadership across the overall Analytics function, with enterprise mandate, deep technical knowledge, and expertise in client interactions to explain complex data analysis.

Responsibilities

• Provide strategic and day-to-day direction on a broad range of complex AML Data Governance program activities, including operational support and addressing/escalating related issues.
• Oversee the timely execution of periodic and event-driven reviews to ensure alignment with regulatory requirements.
• Undertake and complete a variety of complex initiatives requiring seasoned specialist knowledge and/or integration of cross‑functional processes.
• Work independently on analysis, design, and support of technical data management solutions on projects ranging in complexity and size.
• Focus on longer‑range planning for the functional area (12 months or greater) and manage/prioritize multiple projects at a given time.
• Collaborate with business owners to identify opportunities and serve as an ambassador for data science.
• Translate business problems into viable data science solutions using a wide range of programming languages (e.g., Python) and techniques for extracting, preparing data, applying statistics and advanced analytics.
• Visualize insights to tell stories that clearly convey results to decision‑makers and stakeholders at all technical levels.
• Collaborate with data and business analysts, software engineers, data engineers, and application developers to develop scalable, sustainable data science solutions.
• Educate the organization on approaches such as hypothesis testing and statistical validation of results.
• Help the organization understand the principles and math behind the data science process to drive organizational alignment.
• Monitor service, productivity, and efficiency levels within the function and implement continuous process/performance improvements where opportunities exist.
• Lead/facilitate and/or implement action/remediation plans to address performance/risk/governance issues.
• Actively manage relationships across business lines, corporate and/or control functions to ensure alignment with enterprise and/or regulatory requirements.
• Keep abreast of emerging issues, trends, and evolving regulatory requirements and assess potential impacts.
• Participate fully as a team member, support a positive work environment, ensure timely communication of issues/points of interest, and contribute to team development through mentorship.

Requirements

Undergraduate degree or advanced technical degree preferred (e.g., math, physics, engineering, finance, or computer science). Graduate degree preferred with either progressive project work experience or 5+ years of relevant experience; higher‑degree education and research tenure can be counted.

Qualifications

• Extensive experience on AML and financial crimes related regulatory reporting.
• Technical know‑how on SQL and databases.
• Advanced knowledge of best practice data controls to mitigate data risk in the AML space; solid understanding of how data enables AML capabilities/use cases and ability to explain the “so‑what” from an AML risk & control perspective.
• Advanced knowledge of common source‑to‑consumption data pipeline design, leveraging the bank’s data lake and ETL.
• Advanced knowledge of the Three Lines of Defense in a risk management framework.
• Highly organized and diligent individual with ability to manage multiple workstreams.

Skills

• Proficiency in Python and other programming languages for data extraction, preparation, statistics, and advanced analytics.
• Ability to visualize insights and communicate results to stakeholders of varying technical understanding.
• Experience collaborating with cross‑functional partners (data analysts, business analysts, software engineers, data engineers, application developers).
• Knowledge of hypothesis testing, statistical validation, and translating analytical findings into continuous improvement activities.
• Familiarity with enterprise frameworks/methodologies related to the business area.

Benefits

• Base salary and variable compensation/incentive awards (eligibility for cash and/or equity incentive awards through participation in an incentive plan).
• Health and well‑being benefits.
• Savings and retirement programs.
• Paid time off (including Vacation PTO, Flex PTO, and Holiday PTO).
• Banking benefits and discounts.
• Career development opportunities.
• Reward and recognition programs.

Pay

$96,130 – $155,950 USD per year. The base pay actually offered may vary based upon the candidate's skills and experience, job‑related knowledge, geographic location, and other specific business and organizational needs.

Schedule

40 hours per week (full‑time). Domestic travel occasional; international travel never.

We need to ensure we didn't include any boilerplate like "Who We Are", "Our Total Rewards Package" beyond benefits we extracted. We used benefits from that section. We omitted "Additional Information" like colleague development, training & onboarding, interview process, accommodation (these could be considered boilerplate but they are specific about development conversations, training, interview process, accommodation. However the instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The "Additional Information" includes things like colleague development, training & onboarding, interview process, accommodation. Those are not exactly boilerplate but could be considered generic corporate info. However they are substantive about development and interview process. The instruction says "Prefer a few substantive sections over many thin ones." We already have many sections. Might be okay to keep them as part of Benefits or maybe we could add a "Development" section. But we already have Benefits covering career development. The interview process and accommodation could be considered application instructions? Actually accommodation is about disability accommodation, which is EEO-related; might be considered boilerplate. The instruction says remove EEO/equal-opportunity/scam-warning boilerplate. Accommodation statement is related to disability accommodation, which is EEO. So we should remove that. Interview process is maybe application instructions? It says "We’ll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call." That's application instructions; we should remove. Training & Onboarding could be considered part of benefits or development; but it's generic. Might be okay to keep under Benefits? But we already have career development. Could add a "Development" subsection under Benefits? But we should not create thin sections. Perhaps we can incorporate training & onboarding into Benefits as "Training and onboarding sessions". However the instruction says only include sections when posting has real specific content for it. The posting does have specific content about training & onboarding: "We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role." That's specific enough. Could add a bullet under Benefits. Similarly "Colleague Development" includes regular career, development, performance conversations, online learning platform, mentoring programs. That's also specific. Could add bullet under Benefits. Thus we can expand Benefits bullets to include those. Let's adjust Benefits:

• Base salary and variable compensation/incentive awards (eligibility for cash and/or equity incentive awards through participation in an incentive plan).
• Health and well‑being benefits.
• Savings and retirement programs.
• Paid time off (including Vacation PTO, Flex PTO, and Holiday PTO).
• Bank