Solytics Partners - Lead/Manager - Data Science - AML/KYC

Lead/ Manager- Data Science- AML/ KYC

Solytics Partners provides Consulting and Solutions to Banking, Capital Markets, Asset Management, and Insurance firms. We leverage combination of deep domain knowledge, advanced analytics and technology to provide accelerated and efficient services and next generation solutions. Our team of senior consultants comes with significant global experience in key markets and advanced degrees in STEM. Our regulatory compliant solutions and services enable leading financial institutions and corporations to create and sustain competitive advantage.

Education Qualification:

- Bachelor's or Master's degree in Data Science, Statistics, Computer Science, or a related field

- We are seeking a highly skilled AML/Fraud- Lead Data Scientist with strong expertise in technology particularly in R or Python. The ideal candidate will have 5 to 10 years of experience in data science or analytical roles, and with domain knowledge demonstrating proficiency in detecting and preventing fraudulent activities.

Responsibilities:

- Develop and implement models and strategies to identify fraudulent/AML activities and mitigate risks using advanced analytical techniques.

- Utilize R, Python, and other analytical tools to analyze large datasets, identifying patterns and trends related to fraud and AML.

- Model Development: Create, test, and refine predictive models to forecast potential suspicious activities.

- Implement or review systems that monitors and analyze financial transactions, identifying suspicious activities and ensuring compliance with AML regulations.

- Conduct thorough risk assessments and develop risk profiles for clients and transactions to determine potential vulnerabilities.

- Prepare and submit regulatory reports related to AML and fraud, ensuring accuracy and compliance with relevant laws and regulations.

Key Skills:

- 5 to 10 years of experience in data science, analytics, or a related role with a focus on AML and fraud detection.

- Proficiency in R and Python.

- Experience with data analysis tools and techniques.

- Familiarity with machine learning algorithms and statistical models.

- Strong analytical and problem-solving skills with the ability to interpret complex data and make data-driven decisions.

- Domain and practical knowledge on Fraud / AML.

- Relevant certifications in AML, Fraud Detection, or Data Science.

- Knowledge of big data technologies and platforms.

- Familiarity with the financial services industry and its regulatory environment.