Symphony Sensa is breaking new ground in enterprise AI and is looking for Data Scientists to join our AI teams. We have the most advanced machine learning solution to solve hard problems in Anti Money Laundering, Financial Fraud, and Trade Surveillance. At traditional Banks, Exchanges, and for DeFi. You will learn and apply cutting-edge machine-learning techniques developed by our research team. Additionally, you will be contributing to the further advancement of Sensa AI technology through rigorous research and development. As part of a growing team, you will deploy our technology to help our customers solve their biggest and most impactful problems whether it be discovering the Unknown Risks evading their detection systems or reducing the False Positive rate of existing surveillance systems. We combine the rapid agility of a start-up with the financial backing of the world’s largest private AI fund (SymphonyAI). At Symphony Sensa your contribution will make a difference to the world and you will gain experience in one of the top AI companies in the world. Join us now!
- Make research and development contributions to our core product offerings.
- Collaborate on research machine learning white papers.
- Continuously review the latest scientific papers and contribute ideas for future R&D projects.
- Build, evaluate and deploy machine learning models using the Sensa platform.
- Collaborate with AI Researchers in R&D
- Collaborate with other Data Scientists on Sensa deployment projects.
- Support ML and Data Engineers with models and pipeline deployment and configurations.
- Perform data analysis on extremely large tabular data.
- Bachelor’s degree in computer science, information technology, engineering, mathematics, statistics, or physics.
- Deep knowledge of the statistical and mathematical basis of machine learning algorithms.
- High proficiency in Python, Pandas, NumPy, and scikit-learn.
- Ability to contribute to production codebase.
- The capability to work independently in a fast-paced start-up environment.
- The ability to collaborate well with other data scientists and machine learning engineers.
- Willingness to learn new technologies on the job.
- Experience using Github.
- Knowledge of Kubernetes, Kubeflow, Dask, and Rapids.
- Knowledge of Anti Money Laundering, Financial Fraud, and Trade Surveillance