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.

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What You’ll Do

This Associate-level Data Scientist role sits on a Financial Crime / AML & Sanctions analytics team. You will help turn complex data into actionable insights to detect and prevent financial crime using SQL, Python and machine learning approaches.

• Apply SQL and Python to analyse large, structured and unstructured datasets
• Build, validate and (where applicable) help deploy machine learning models for AML, sanctions screening and fraud detection
• Explore NLP and foundation-model (LLM) techniques for transaction / alerts triage
• Support data preparation, feature engineering and evaluation metric design
• Contribute to research, create reproducible analyses, and document results for stakeholders
• Work with cross-functional teams and client contacts to translate technical findings into business recommendations
• Follow professional, ethical and regulatory standards in all analyses

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What You Must Have (Minimum Qualifications)

• Bachelor’s degree in Computer/Information Science, Economics, Statistics, Mathematics, Engineering, Operations Research, Data Science or a related quantitative field
• ~1 year of hands-on experience in data science or machine learning work (internship/industry/project experience acceptable)
• Practical experience with SQL for complex queries and data wrangling
• Proficiency in Python for data manipulation and analysis

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Nice to Have / What Sets You Apart

• Interest or experience in financial crime, AML, sanctions, KYC, or fraud analytics
• Experience with scikit-learn, XGBoost and modern NLP/transformer toolkits (e.g., Hugging Face)
• Familiarity with CI/CD practices for data science (notebooks -> production pipelines)
• Exposure to model evaluation metrics, model explainability and monitoring
• Comfort working with both structured and unstructured data sources
• Prior experience exploring agentic AI frameworks or LLM-assisted workflows

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Compensation & Benefits

• Salary range: $63,000 - $140,000 (actual compensation depends on experience, location, and applicable employment laws)
• Eligible for annual discretionary bonus
• Our client provides a competitive benefits package (examples may include medical, dental, vision, retirement/401(k), paid time off and parental leave — benefits vary by location)

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Location, Work Authorization & Hiring Policies

• Primary work location: Grand Central / New York, NY (onsite or hybrid as defined by the client)
• Candidates must be authorized to work in the U.S.; the client may have specific policies regarding visa sponsorship — please review the client policy or contact Careertakes for details
• For applicants in jurisdictions with Fair Chance / Ban-the-Box laws (e.g., certain California local ordinances), the client will follow applicable local rules regarding criminal history in hiring decisions

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How We Evaluate Candidates

We evaluate applicants based on demonstrated technical skills (SQL, Python), problem-solving ability, curiosity about financial crime analytics, and cultural fit. Submissions that include relevant project samples, code snippets or model evaluations (shared securely) help speed review.

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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.