Principal Data Science Engineer - Financial Crimes Models & Analytics

About the position 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. You will work with business partners across various domains to acquire data, perform data analysis, and build new features to improve our detection. You will also work with machine learning models, rewrite legacy models, and support the data preparation for our reporting efforts. Additionally, you will strive to simplify our infrastructure and production support complexity. Your role will include 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, and bringing on the latest implementations of emerging technologies into Fidelity's Financial Crimes Detection Program. You will also be responsible for detecting suspicious activity occurring on Fidelity's platform, supporting Fidelity's new business initiatives, and helping to develop and advance your teammates by sharing your experience, expertise, and perspective.

Responsibilities

• Own the development of data pipelines that support next generation surveillance solutions.
• Work with business partners to acquire data, perform data analysis, and build new features.
• Work with machine learning models and rewrite legacy models.
• Develop model performance metrics and make model adjustments.
• Identify bad actors or victims on the platform.
• Implement emerging technologies into Fidelity's Financial Crimes Detection Program.
• Detect suspicious activity on Fidelity's platform.
• Support Fidelity's new business initiatives.
• Share experience and expertise with teammates.
• Collaborate across Financial Crimes Compliance to understand red flags and risks.
• Develop features using technologies like DBT, Snowflake, and Python.
• Assist in architectural design and implementation of the transaction monitoring platform.
• Lead the transformation of AI/machine learning algorithms into production-ready processes.
• Create robust testing scenarios including unit testing and regression testing.
• Provide technical leadership and mentoring to team members.
• Explore modern technologies and determine their applicability.

Requirements

• Bachelor's degree in computer science or equivalent technical expertise.
• Minimum of 6+ years of software or data engineering experience.
• Excellent proficiency in Python or PySpark.
• Big data experience with Snowflake or Hadoop.
• Experience working with DBT or Databricks is a plus.
• Proficient in designing and developing data pipelines and scalable architectures.
• Experience in the software development cycle from design to implementation.
• Excellent proficiency in querying relational and non-relational databases.
• Strong understanding of digital assets and blockchain technologies.
• Experience developing pipelines that support AI/Machine Learning processes is a plus.
• Familiarity with distributed systems such as Apache Iceberg or Snowflake.
• Familiarity with ML algorithms such as decision trees and clustering.
• Experience in the Financial Services industry, particularly in Financial Crimes.

Nice-to-haves

• Experience developing pipelines that support AI/Machine Learning processes.
• Prior experience in the cryptocurrency space.

Benefits

• Comprehensive health care coverage.
• Emotional well-being support.
• Market-leading retirement.
• Generous paid time off.
• Parental leave.
• Charitable giving employee match program.
• Educational assistance including student loan repayment and tuition reimbursement.

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