Data Scientist, Financial Crimes - USDS

Position Overview
As a Financial Crime Data Scientist, you will play a crucial role in leveraging machine learning, analytics and visualization techniques to enhance our organization's capabilities in detecting and preventing financial crimes. You will be responsible for analyzing large datasets, developing machine learning models, and creating visualizations to identify patterns, anomalies, and potential risks related to money laundering, fraud, and sanctions violations. This role offers an exciting opportunity to apply advanced technology solutions to combat financial crime and ensure regulatory compliance.

Responsibilities
- Develop, implement, and optimize machine learning models to detect money laundering, fraud, and other financial crimes, leveraging techniques such as anomaly detection, clustering, and predictive modeling.
- Analyze large volumes of transactional and user data to identify suspicious patterns or behaviors indicative of financial crimes.
- Perform data analysis to support the transaction monitoring, sanction, KYC and high-risk investigation teams, including performing ad-hoc data analysis, that assist Financial Crime Compliance leadership in decision-making and strategic planning processes.
- Design and implement data visualization dashboards and reporting tools to communicate insights and findings from financial crime detection efforts.
- Collaborate with internal stakeholders to design, develop, validate, and implement AML scenarios, and conduct threshold tuning to optimize performance.
- Document and manage projects related to threshold tuning, scenario design, and detection methodologies.
- Collaborate with cross-functional teams, including product, engineering, and data science, to integrate machine learning solutions into existing systems and processes.
- Perform special projects, and additional duties and responsibilities as required.

Qualifications

Minimum Qualifications:
- Bachelor's degree in Computer Science, Data Science, Statistics, or a related field.
- 2+ years of experience in data analysis, machine learning, or data visualization, with a focus on financial crime compliance or related domains.
- Strong analytical skills and the ability to work with large datasets to extract actionable insights.
- Demonstrate strong critical thinking skills, with the ability to analyze complex problems, evaluate information objectively, and communicate well-reasoned conclusions based on evidence and logic.

Preferred Qualifications:
- Proficiency in programming languages such as Python or R, as well as experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with data visualization tools and techniques for creating interactive dashboards and reports (e.g., Tableau, Power BI, matplotlib).
- Familiarity with big data technologies and distributed computing platforms (e.g., Hadoop, Spark).
- Experience working with transaction monitoring, sanction screening or KYC technologies, with knowledge of financial crime compliance regulations and methodologies, including anti-money laundering (AML) and know your customer (KYC) requirements.
- Strong communication skills and the ability to translate technical concepts into clear and concise insights for non-technical stakeholders.

Job Information

[For Pay Transparency] Compensation Description (annually)

The base salary range for this position in the selected city is $98800 - $196000 annually.

Compensation may vary outside of this range depending on a number of factors, including a candidate's qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

The Company reserves the right to modify or change these benefits programs at any time, with or without notice.

For Los Angeles County (unincorporated) Candidates:

Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:

1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;

2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and

3. Exercising sound judgment.