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We are looking for a Senior Data Scientist to join our team.
This job is about turning data into actionable knowledge, which requires a blend of scientific, problem-solving, analytical, technical, and communication skills. The role is primarily focused on (but not limited to) solving business problems in the technological domain of Data Science.
Responsibilities
- Identify business problems, find the right data and methods to address them
- Process large volumes of structured and unstructured customer data using advanced analytical solutions
- Turn analyzed data into unique actionable insights and business value
- Create high-quality data visualizations
- Create data pipelines for feature engineering, missing values treatment, outliers' detection, etc
- Perform research, build, and validate analytical, mathematical, econometric, descriptive, and predictive models that deliver better decisions across a broad range of industries and data sources
- Estimate, plan and coordinate the delivery of moderate/large sized projects
- Evaluate and select the best matching Data Science tools and libraries
- Present findings in a clear and informative way
- Communicate effectively with different departments and roles (stakeholders, product managers, engineers) to discuss complex data-driven findings and technical matters
- Continuously develop knowledge base within the Data Scientists team, participate in common brainstorming sessions
- Educate junior and middle Data Scientists
Requirements
- 3+ years of relevant experience working with a variety of information systems and data
- Writing high-quality Python code according to PEP-8 guidelines
- Strong knowledge of various data exploration and analysis techniques, ability to build models or analytical frameworks, develop hypotheses, and design experiments
- Advanced knowledge in one of the domains: Computer Vision, Time Series, Natural Language Processing, Recommendation Systems, Predictive Analytics
- Knowledge of EDA, classical vs advanced Machine Learning models, model performance metrics and losses, model fine-tuning
- Knowledge of pros&cons for SOTA ML architectures and applicable use cases for them
- Understanding of ML projects' life cycle and ability to follow methodology processes (CRISP-DM, TDSP, LeanDS, etc.) used in data science projects
- Ability to design and supervise data labeling process
- Ability to interpret and report results of analyses, provide business recommendations; ability to coach and train others
Nice to have
- Strong academic background, Bachelor's / Master's Degree in Computer Science, Math, Applied Statistics, or a related field
- Machine Learning Engineering mindset, experience with Docker, Linux, CI/CD, MLflow, etc
- Projects completed using different methodology/models or knowledge of one of the Deep Learning frameworks (PyTorch, TensorFlow)
- Experience with ML services of cloud providers: AWS, Azure, or GCP
- Experience with PySpark
- Some experience in ML project technical leadership