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Data Science Specialist
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**¿Who we are?**
A financial technology company dedicated to supporting the small and medium-sized companies in Mexico, developing and offering solutions to solve their main problems, and seeking to be the best ally of entrepreneurs with dreams and ambitions to create value, consolidate their well-being and contribute to the community, the country and the planet.
**Responsibilities**:
- Find and implement the right algorithms and tools for NLP tasks, also, develop and design NLP systems and architectures according to requirements
- Syntactic & Semantic Parsing.
- Perform statistical analysis of results and refine models.
- Maintain NLP libraries and frameworks.
- Enhancing data collection procedures to include information that is relevant for building analytic systems.
- Interact cross-functionally, making business recommendations with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information, informing decision-making.
- Work to solve defined problems with a completely flexible approach and being mostly self-managed.
- Collaborate with data engineers and ML engineers, as well as with internal temas and clients.
- Help define the analytical direction and influence the direction of the associated engineering and infrastructure work.
- Document the methodology used, results obtained, in a clear manner for reproducible research and help other team members to solve problems in a faster way.
- Train and mentor junior team members (Data & ML engineers and other Data Scientists).
**Experience Required**:
- Master's degree in a quantitative discipline (e.g. Computer Science, AI, Machine Learning, Mathematics, Physics, Electrical Engineering, Industrial Engineering) or equivalent practical experience. 3+ years of work experience in data analysis related field.
- Experience with statistical software (e.g., Python, pandas) and database languages (e.g., SQL).
- Experience working with Data Science/Machine Learning software and libraries such as TensorFlow, Keras, Pytorch, scikit-learn, etc.
- Having a strong understanding of NLP techniques in areas of text representation, semantic extraction techniques, data structures, and modeling is essential. Also be able to effectively design software architecture.
- Be familiar with LSTM, encoder-decoder and Transformers architectures.
- Experience designing and building ad-hoc DNN architectures or statistical models as well as data-efficient preprocessing pipelines.
- Be capable of adapt model architectures and re-train them using transfer learning techniques to adapt them for specific domains.
- Understanding of text representation techniques, algorithms, statistics 1+ years of production programming experience in Python.
**Nice to have**:
- Any other related experience with Big Data, artificial intelligence, machine learning and/or deep learning, predictive analytics.
- Experience with Cloud Providers (AWS).
- Experience with GitLab CI/CD or equivalent.
- 3+ years of production programming experience in Python.
- Applied experience with machine learning on large datasets.
- Experience working with other sources of language such as picture or audio.
