Develop ML focused solutions for the financial sector using best-of-breed tools combining ThetaRay 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.

Чем Вы должны обладать

Обязательно

3+ 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 NTSdata-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.