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Machine Learning Specialist
Il y a 3 mois
Our esteemed client, a leading entity in the financial sector, is seeking a Data Scientist to contribute to their innovative projects with an initial contract until the end of 2024, with potential for extension. Below are the details of the role.
Role Overview
- Design and execute data science applications, utilizing both supervised and unsupervised machine learning methodologies.
- Work collaboratively with interdisciplinary teams to uncover business prospects related to financial crime prevention.
- Determine necessary data, gather it, and perform essential data preparation tasks such as cleansing and enrichment for effective processing.
- Develop predictive models to evaluate and prioritize alerts generated by current and future anomaly detection systems.
- Create algorithms for anomaly detection employing machine learning models or relevant analytical techniques, including Natural Language Processing and graph/network analysis.
- Analyze interactions within our ecosystem of stakeholders (clients, agents, beneficial owners, etc.) using graph databases and network analytics to identify unexpected and potentially hazardous relationships.
- Continuously enhance model performance in close partnership with subject matter experts.
- Craft both static and interactive data visualizations to effectively communicate your findings to stakeholders who may not have a robust data science background.
Key Responsibilities:
- Re-calibrate scenario parameters for NetReveal.
- Conduct quantitative assessments on enhancements in our Anti-Money Laundering (AML) scenarios, including Above-The-Line testing and minimizing overlapping alerts.
- Enhance investigation tools.
- Formulate a strategy and roadmap to refine current investigation tools for AML NetReveal alerts.
- Develop an insights dashboard to monitor trends and KPIs related to financial crime, market abuse, and sanction circumvention.
- Implement solutions to reduce false positive alerts from NetReveal.
- Automate the resolution of false positive hits from Norkom.
- Conduct a proof of concept for a solution to automatically manage large volumes of false positive hits generated by our sanction screening process, alongside other data initiatives to boost overall efficiency.
Required Technical Skills:
- A Master's or PhD in a quantitative discipline (e.g., computer science, artificial intelligence, mathematics, physics, statistics).
- At least 2 years of experience in developing machine learning models.
- Proficient programming skills in Python, SQL, and Spark.
- Expertise in Scikit-learn and Pandas libraries.
- Strong understanding of data science techniques and their application in a business context.
Preferred Qualifications:
- Experience in creating data products from conception to deployment.
- Familiarity with tools such as Power BI, the Hadoop ecosystem, and Git.
- Proficiency in visualization libraries/tools (e.g., Plotly/Dash/NetworkX).
- Knowledge of network analytics.
- Understanding of compliance-related domains (sanctions, transaction monitoring, KYC, fraud detection) preferably within the financial industry.
- Exposure to generative AI and/or Natural Language Processing.
- Familiarity with cloud platforms, ideally Azure.
Compensation:
Competitive daily rate based on experience.
Job Type:
Contract position.
