Data Science Engineer (NLP)
About the project
Quantum is a technology company that transforms big data and data science models into data analytics solutions. It develops solutions using a modern cloud ecosystem and architecture approaches. The company works with enterprises and growing startups all around the world to deliver best-in-class services.
Our client is a digital transformation, cognitive computing, artificial intelligence software company. Their product is a highly scalable and customizable platform that serves as an AI Operating system. This system is used for a wide range of capabilities such as business intelligence, decision making, forecasting and situational awareness. The product also contains cognitive computing applications configured for specific industries and business functions.
Skills and qualification:
- At least 4 years of commercial experience in DS;
- Strong knowledge of linear algebra, calculus, statistics and probability theory;
- Knowledge and experience with algorithms and data structures;
- Experience with Machine Learning libraries (NumPy, SciPy, Pandas, ScikitLearn);
- Experience in Natural Language Processing;
- Experience with at least one of Deep Learning frameworks (Tensorflow, Keras, PyTorch);
- Experience with SQL;
- Experience with Cloud Computing Platforms (AWS, GCloud, Azure);
- Strong knowledge of OOP;
- At least Upper-Intermediate (written and spoken) level of English.
Would be a plus:
- Participation in Kaggle competitions;
- Knowledge of modern Neural Networks architectures (DNN, CNN, LSTM, etc);
- Experience in classical Computer Vision algorithms;
- Experience with production ML/DL frameworks (OpenVino, TensorRT, etc.);
- Docker practical experience;
- Basic understanding of Big Data concepts.
- Data Analysis and Preparation;
- Development of NLP/Deep Learning / Machine Learning / Computer Vision solutions;
- You will be working on full-cycle data science projects. Your tasks will include data preparation, developing ML models and deploying them to production. Sometimes, this will require the ability to implement methods from scientific papers and apply them to new domains.
- Exchange of experience, professional development;
- A strong team, a healthy atmosphere;
- Flexible working time;
- 20 days paid vacation;
- Paid sick leave;
- 8-hour working day and 5-day working week;
- English lessons and massage service in the office (partially paid by the company);
- Opportunity to take part in conferences, meetups etc. (fully or partially paid by the company);
- Regular company events.