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Data Scientist III - FCRM Risk Modeling

TD
Mount Laurel, USA
Full-time
Onsite
USD 96130-155950 yearly
Discovered 3 weeks ago
PythonSQLStatisticsRegressionClassificationMachine learning

Full Job Posting

Work location and hours

  • The listed work location is Mount Laurel, New Jersey, United States of America.
  • The posting states 40 hours; it does not specify a remote, hybrid, or onsite policy.

Pay

  • The stated pay range is $96,130 to $155,950 USD per year; actual base pay may vary based on skills, experience, job-related knowledge, location, and business needs.

Role overview

The Data Scientist III provides technical leadership across analytics and deep expertise in explaining complex data analysis.

The role works on financial-crime risk modeling and advanced analytics for TD's U.S. Financial Crime function.

Financial-crime analytics

  • Develop, maintain, and enhance enterprise AML/CTF models and AI solutions to address regulatory changes, internal policies, global strategy, emerging risks, and industry practices.
  • Work across customer rating, sanctions screening, transaction monitoring, emerging risk, model performance monitoring, analytics, and reporting.
  • Partner with business owners to identify opportunities and translate business problems into data-science solutions.
  • Extract and prepare data, apply statistics and advanced analytics, and generate insights from large datasets.
  • Visualize findings and explain results to decision-makers and stakeholders at varying technical levels.
  • Collaborate with data and business analysts, software engineers, and other partners.

Education and experience

  • An undergraduate or advanced technical degree in math, physics, engineering, finance, or computer science is preferred; graduate education is also preferred.
  • The posting refers to five or more years of relevant experience, or graduate education and research tenure that may be counted; the source wording is incomplete.

Preferred and required skills

  • Python and SQL proficiency are required.
  • The posting lists statistics, regression, classification, machine learning, anomaly detection, numerical intuition, and evaluation of model outputs, data quality, and performance tradeoffs.
  • Financial-crime or compliance risk analytics experience is a plus.
  • Hands-on GenAI experience, including LLM fine-tuning or prompting, is a strong plus; LLM APIs and GenAI-based data-labeling solutions are mentioned.

Eligibility

  • Applicants must be U.S. citizens or lawful permanent residents and must not require current or future TD sponsorship; the role is not eligible for work visa sponsorship.

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