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Fidelity Investments

Principal Data Science Engineer - Financial Crimes Models & Analytics

Job Posted 10 Days Ago Posted 10 Days Ago
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5 Locations
85K-179K Annually
Senior level
5 Locations
85K-179K Annually
Senior level
As Principal Data Science Engineer, you will develop data pipelines and machine learning models to combat financial crimes, especially in cryptocurrency. You will lead teams, enhance detection capabilities, and collaborate with various business partners.
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Job Description:

The Role

Principal Data Science Engineer – Financial Crimes Models & Analytics

Fidelity is seeking to hire a seasoned Principal Data Science Engineer to join our Financial Crimes Models & Analytics team to assist with the ongoing transformation of the firm’s Financial Crimes Compliance program, especially in the cryptocurrency space. If you are enthusiastic about data engineering, data science, and technology to help fight financial crime, then this is an excellent opportunity for you! As Principal Data Engineer, you will be:

  • Responsible for owning the development of data pipelines that support next generation surveillance solutions on a wide range of anti-money laundering typologies, primarily supporting the team’s work in the digital assets space.
  • Working with business partners across various domains to acquire data, performing data analysis, and building new features to improve our detection.
  • Working with machine learning models, rewriting legacy models, and supporting the data preparation for our reporting efforts. You will also strive to simplify our infrastructure and production support complexity.
  • Developing model performance metrics and making model adjustments accordingly to ensure models are performing optimally. 
  • Protecting Fidelity’s customers and brand by identifying bad actors or victims on the platform.
  • Bringing on the latest implementations of emerging technologies into Fidelity’s Financial Crimes Detection Program.
  • Detecting suspicious activity occurring on Fidelity’s platform 
  • Supporting Fidelity’s new business initiatives, e.g., Fidelity Digital Assets. 
  • Helping to develop and advance your teammates by sharing your experience, expertise, and perspective. 
  • Collaborating across Financial Crimes Compliance to understand the various red flags and risks that our models attempt to detect, especially in the cryptocurrency space.
  • Developing features using various technologies, including DBT and Snowflake, as well as Python.
  • Assisting in the architectural design and implementation of the transaction monitoring platform that enables and scales Fidelity’s newest business initiatives, including digital assets and other emerging technologies.
  • Lead the transformation of experimental AI/machine learning algorithms into scalable, robust production-ready processes. 
  • Create robust testing scenarios, including unit testing, regression testing, and model performance. 
  • Provide technical leadership, mentoring and training to other team members through code reviews, collaboration, and educational presentations. 
  • Explore modern technologies, emerging trends and determine their applicability to the team’s use cases; orchestrate the adoption of such technologies and trends where appropriate. 

The Expertise and Skills You Bring  

  • Bachelor's degree in computer science or equivalent technical expertise 
  • Possess minimum of 6+ years of software or data engineering experience, including prior experience leading and delivering complex data engineering projects. 
  • Possess excellent proficiency in Python or PySpark, required.
  • Possess big data experience with Snowflake or Hadoop, required.
  • Experience working with DBT (data build tool) or Databricks is a plus.
  • Experienced and proficient in designing and developing data pipelines, scalable architectures, and data modeling. 
  • Experience in the software development cycle from design to implementation to testing, CI/CD, version control management/git, documentation, etc. 
  • Excellent proficiency in querying relational databases, e.g., Oracle, Snowflake, and non-relational databases, e.g., MongoDB 
  • A strong understanding of digital assets and blockchain technologies; Prior experience in the cryptocurrency space is a plus. 
  • Experience developing pipelines that support AI/Machine Learning processes nice to have,
  • Familiarity with a distributed system such as Apache Iceberg or Snowflake 
  • Familiarity with ML algorithms such as decision trees, autoencoders/neural networks, linear/logistic regression, clustering, etc. 
  • Experience in the Financial Services industry, Financial Crimes space particularly desirable.
  • You are thoughtful in the approach and design of technology solutions. 
  • You are committed to working with our business partners, systems analysts, data engineers, and data scientists to build the best system possible. 
  • You adhere to and enforce engineering best-practices (Git, documentation, test automation).
  • Love of technology — following trends and trying them in small scale to see how they work. 
  • Have an eye for detail and are committed to quality and ambitious standards.
  • Command excellent oral and written communication skills.
  • Flexible, willing to try new things and shift priorities as necessary. 
  • Good foresight with the ability to anticipate problems and plan out solutions. 

The Team 

The Financial Crimes Models & Analytics team within Fidelity’s Enterprise Compliance group is responsible for the design, development, and optimization of Fidelity's Financial Crimes detection models. We partner with colleagues across Fidelity to build software and data solutions that support Fidelity’s Financial Crimes Compliance programs. 

Our team has broad responsibility for Fidelity Investments transaction monitoring across multiple business units. Coverage areas include Cryptocurrency Trading and Blockchain Forensics, Insider Trading, Terrorist Financing, International Money Movement, Global Sanctions & Anti-Corruption, Elder Financial Exploitation, Negative Media screening, Market Manipulation, Securities Fraud, Low-Priced Securities, etc. Our team collects and curates data and applies machine learning and emerging technologies to improve Fidelity’s surveillance and screening capabilities. 

The base salary range for this position is $85,000-$179,000 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.

Fidelity’s hybrid working model blends the best of both onsite and offsite work experiences. Working onsite is important for our business strategy and our culture. We also value the benefits that working offsite offers associates. Most hybrid roles require associates to work onsite every other week (all business days, M-F) in a Fidelity office.

Certifications:

Category:Information Technology

Top Skills

Databricks
Dbt
Hadoop
MongoDB
Oracle
Pyspark
Python
Snowflake

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