AML/Sanctions- Data Scientist- Associate
The AML/Sanctions Data Scientist Associate at Confidential Client applies advanced data science and machine learning techniques, including SQL and Python, to address financial crime challenges such as AML and fraud analytics. This role involves client engagement, developing strategic insights, and contributing to innovative solutions within a collaborative team environment while upholding professional and ethical standards.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Accounting & Finance.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
The Opportunity
AML Sanctions Data Scientist Boston, MA — Join Confidential Client’s Financial Crime Unit as an Associate data scientist focused on AML, sanctions screening and fraud analytics. In this role you’ll work with SQL and Python to analyze complex transactional datasets, support client engagements, and help build ML/NLP solutions that address real financial crime challenges.
What You’ll Do
- Use SQL and Python to extract, clean, and analyze structured and unstructured data relevant to financial crime detection.
- Build, evaluate, and deploy machine learning models (classification, anomaly detection, ranking) to surface AML and sanctions risks.
- Experiment with NLP and LLM-based approaches for entity resolution, transaction narrative analysis, and alert triage.
- Contribute to end-to-end data science workflows, including model validation, monitoring, and CI/CD for deployment.
- Support client engagements: translate technical results into actionable insights, prepare presentations, and communicate findings clearly.
- Collaborate with stakeholders (analysts, engineers, compliance experts) to refine requirements and deliver solutions that meet regulatory standards.
- Participate in research, prototyping, and knowledge-sharing to advance team capabilities and maintain professional standards.
Qualifications (Minimum)
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Data Science, Economics, Engineering, or a related quantitative field.
- ~1 year of professional experience in data science or machine learning (internships and relevant project experience count).
- Strong SQL skills for complex queries and data transformation.
- Proficient in Python for data manipulation and model development.
- Familiarity with common ML libraries (scikit-learn, XGBoost) and foundational ML concepts and evaluation metrics.
- Ability to communicate technical concepts clearly to non-technical stakeholders.
Preferred / Nice-to-Have
- Interest or experience in AML, sanctions, fraud detection, or financial crime analytics.
- Hands-on experience with NLP/transformer frameworks (e.g., Hugging Face) or LLM-based approaches.
- Experience with model CI/CD, deployment pipelines, and MLOps best practices.
- Comfort working with both structured and unstructured data sources.
- Exposure to modern data engineering tools and cloud platforms is a plus.
Compensation & Benefits
- Salary range: $63,000 - $140,000 (actual compensation will depend on skills, experience, qualifications and location in accordance with applicable laws).
- Eligible for an annual discretionary bonus.
- Benefits typically include medical, dental, vision, retirement (401k), paid holidays, vacation, and sick leave. Specific plans vary by location and hire status.
Location & Employment Type
- Office location: Boston, MA (postal code 02133). This is a full-time position.
- All hiring and employment-related decisions will comply with applicable federal, state, and local laws (including fair-chance and pay-transparency requirements where applicable).
Why Apply via Careertakes
- Careertakes is a third-party recruiting platform — you may receive access to additional matched roles.
- We follow best practices used by third-party recruiters: transparent job details, fair evaluation, and timely communication.
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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