Principal Data Science Engineer - Financial Crimes

Fmr LLC
Jersey City, NJ, United States
3 months ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
6 years minimum
Compensation
$107,000.0 - $216,000.0
Working hours
Regular working hours
Job source

Tech stack

Artificial Intelligence Data Analysis Artificial Neural Networks Automation of Tests Cluster Analysis Code Review Continuous Integration Information Engineering Data Transformation Data Visualization Relational Databases Digital Assets
+17 more
Information Retrieval Python (Programming Language) Machine Learning MongoDB Oracle (Applications) SQL Databases Transaction Data Feature Engineering Large Language Models Snowflake Data Build Tool (dbt) Model Validation Generative AI Information Technology Non-relational Database Machine Learning Operations Data Pipelines

Job description

Financial Crimes Models & Analytics is seeking a Principal Data Science Engineer to lead the design, development, and optimization of our transaction monitoring surveillance models.

You will partner with our Data Scientists, Business Intelligence analysts, Investigators, and Compliance professionals to translate regulatory requirements into scalable, rules based & machine learning detection models. This role requires a unique blend of banking, brokerage, anti-money laundering (AML) & fraud knowledge, as well as data analysis, data engineering, and AI/ML expertise.

If you’re passionate about feature engineering, analytics, and machine learning to help fight financial crime, this is an excellent opportunity for you!, * Collaborate with team members and compliance partners to understand AML typologies and red flags we must detect

  • Assist in building detection models and features using SQL, Python, DBT (Data Build Tool), and Snowflake
  • Develop detection models using both rules-based and machine learning algorithms on customer, account, and transaction data
  • Apply machine learning and AI techniques to enhance suspicious activity detection by analyzing and identifying appropriate target data.
  • Monitor and optimize model performance using proper ML Operations tools
  • Help drive AI use cases for investigative workflows including integration in alert management systems, narrative generation, and straight through SAR filing
  • Champion best practices for CI/CD, robust automated testing, model performance, and production monitoring
  • Provide technical leadership, mentoring and training to other team members through code reviews, collaboration, and educational presentations
  • Explore new technologies (e.g., anomaly detection, graph analytics, predictive modeling) and determine their applicability to the team’s use cases; orchestrate the adoption of such technologies and trends where appropriate

Requirements

  • Bachelor’s degree in Computer Science or equivalent technical discipline.
  • 6+ years of experience in software or data engineering, including leading and delivering complex projects.
  • Strong proficiency in Python or at least one object-oriented programming language (e.g., Java) with a focus on writing clean, modular, and testable code.
  • Strong experience querying relational databases (e.g., Oracle, Snowflake) and working with non-relational databases (e.g., MongoDB).
  • Hands-on experience with machine learning algorithms, including decision trees, neural networks, regression models, clustering, and anomaly detection.

Preferred Skills

  • Domain expertise: Prior experience working with customer and transactional data in the fraud or AML space.
  • Digital assets knowledge: Understanding blockchain technologies; prior experience in cryptocurrency monitoring is a plus.
  • Experience with dbt (data build tool) for data transformation and pipeline development.
  • Prior experience developing solutions using large language models (LLMs), including Retrieval-Augmented Generation (RAG) for information retrieval and workflow automation.
  • Certifications such as CAMS (Certified Anti-money Laundering Specialist) or CFE (Certified Fraud Examiner) are desirable

Benefits & conditions

$107,000 - $216,000 a year

Loan repayment program, Tuition reimbursement, Parental leave, Paid time off Monday to Friday, Financial Crimes Models & Analytics is made up of Data Scientists, Data Engineers, Business Intelligence, and Data Visualization analysts. Our team has broad responsibility for Fidelity Investments transaction monitoring across multiple business units, including Brokerage and Digital Assets. We leverage data to detect potential suspicious activity, customer behavior changes, and more.

Coverage areas include insider trading, high risk money movement, customer behavior & potentially suspicious transactional patterns, elder financial exploitation, low-priced securities, emerging risks, cryptocurrency transactions and many more. The base salary range for this position is $107,000-216,000 USD per year.

Placement in the range will vary based on job responsibilities and scope, geographic location, candidate’s relevant experience, and other factors.

Base salary is only part of the total compensation package. Depending on the position and eligibility requirements, the offer package may also include bonus or other variable compensation.

We offer a wide range of benefits to meet your evolving needs and help you live your best life at work and at home. These benefits include comprehensive health care coverage and emotional well-being support, market-leading retirement, generous paid time off and parental leave, charitable giving employee match program, and educational assistance including student loan repayment, tuition reimbursement, and learning resources to develop your career. Note, the application window closes when the position is filled or unposted.

Please be advised that Fidelity’s business is governed by the provisions of the Securities Exchange Act of 1934, the Investment Advisers Act of 1940, the Investment Company Act of 1940, ERISA, numerous state laws governing securities, investment and retirement-related financial activities and the rules and regulations of numerous self-regulatory organizations, including FINRA, among others. Those laws and regulations may restrict Fidelity from hiring and/or associating with individuals with certain Criminal Histories.

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