Data Scientist

Intro:

Key responsibilities:

• Implementing statistical and machine learning methods that could be used to solve a given problem, then evaluating and presenting the results
• Data acquisition, exploration, cleaning, augmentation, and visualization
• Designing, conducting, and tracking experiments in different domains
• Analysing and addressing the errors of applied machine learning models and algorithms
• Participating in solution productization, high-level design, and low-level implementation
• Driving technical quality of a solution and managing technical debt
• Ensuring that the solutions are well-documented and presentable to the stakeholders
• Participating in the technical investigation (Spike) and prototyping (PoC)
• Communicating and collaborating with engineering teams, product teams, and stakeholders in all project phases

Required Qualifications:

• Demonstrated proficiency in designing and delivering robust and scalable distributed systems in production
• Proficient in:
• statistical data analysis
• supervised and unsupervised machine learning
• transfer learning and ensemble learning
• feature engineering
• optimization techniques
• Proficient in at least one of the commonly used frameworks – TensorFlow, PyTorch, Keras, scikit-learn, etc.
• Experienced in working with structured and unstructured data, relational and non-relational databases
• Experienced with Python and familiar with object-oriented programming, clean coding, and version control
• Familiarity with algorithmic complexity, GPU/CPU utilization, and I/O bandwidth
• Creates pragmatic technical documentation with well-understood diagrams
• Able to explain technical points using business language and presentations

Nice to have:

• Striving for constant improvements in solution design
• Keeping up with the new trends in the field
• Experienced in building solutions based on deep learning models
• Experienced in working with some of the following data types: images, text, time series, spatial data, etc.
• Experienced with cloud platforms