• Develop ML focused solutions for the financial sector using best-of-breed tools combining company unique algorithms with frameworks such as spark, MLflow, Airflow, etc. in cloud native environments
• Design and implement methods to assess the quality of unsupervised and semi-supervised results with key metrics as well as thorough investigation
• Participate in research and technology innovation to develop more efficient and automated ways to handle ML/DL workloads
• Participate in new product/feature definitions and implementation
• Work mostly with Python/Spark on Kubernetes environments
• 2+ years of experience as a data scientist
• Experience in defining and implementing feature engineering processes for ML based products
• Experience in writing code in Python (and Pyspark) and using Python data-science frameworks
• BSc/BA in Mathematics, Physics, Computer Science, Economics, or another related field
• Experience with building solutions with Big Data tools and frameworks such as Spark, Hadoop, etc
• Experience in developing machine learning oriented solutions for the financial sector - advantage
• Experienced with machine learning framework such as Sklearn - a must, TensorFlow/Keras - advantage
• Experience with NLP - an advantage
• Experience with Graph Algorithms - an advantage
• Great communication skills
• Ability to quickly learn new technologies, frameworks, and algorithms
• Very good English, written and verbal
• distant work
Company is the leading provider of AI-based Big Data analytics.
We are dedicated to helping financial organizations combat financial crimes through money laundering facilitating malicious crimes such as terrorist financing, narco-trafficking, and human trafficking which negatively impact the global economy.
Our Unsupervised and Semi-Supervised Intuitive AI solutions enable clients to manage risk, detect money laundering schemes, uncover operational issues, and reveal valuable new growth opportunities.
In the resume, indicate the desired level of salary. Job Code 9583