Senior Machine Learning Engineer, Trust & Safety

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Requirements:

• 4+ years of work experience in analytics and data science domain focusing on financial services-related business problems
• 3+ years of experience deploying statistical and machine learning models in production
• 2+ years of experience in integrating data science models into applications
• Proven experience in developing and deploying ML models at scale, with a deep understanding of model lifecycle management.
• Knowledge and experience of crypto exchange trading, financial markets, or banking
• Extensive knowledge of ML lifecycle management tools (Sagemaker, ML Flow, or similar ones), libraries, data structures, data modeling, and software architecture
• Advanced skills with SQL are a must
• Proficient in Python
• Experience with one or more big data tools and technologies like Snowflake, Databricks, S3, Hadoop, Spark
• Experienced in working collaboratively across different teams and departments
• Strong technical and business communication

Responsibilities:

• Design and develop Trust & Safety machine learning and AI models to optimize across fraud, crypto exchange trading, and anti money laundering.
• Distill complex models and analysis into compelling insights for our stakeholders and executives
• Analyze large and complex datasets to identify patterns for feature engineering, trends, and anomalies and develop predictive models that can be used for decision-making.
• Collaborate with software developers to design and implement machine learning systems that can improve the speed and accuracy of the machine learning models.
• Monitor and analyze the performance of our machine learning models and systems and make necessary improvements to ensure their effectiveness.
• Stay up-to-date with data science tools and methodologies in technology and financial domain
• Perform root cause analysis and resolve production and data issues