Job Requirements
Skills
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Job description for Data Science Engineer (REMOTE) at Cognotiv
- Create prototype with Simulated data sets.
- Set up and manage our AI development and production infrastructure, subsequently deploy AI models into production.
- Design data modeling processes to create algorithms and predictive models and perform custom analysis.
- Help business stakeholders understand the potential and limitations of AI when planning new products.
- Build data ingest and data transformation infrastructure.
- Identify transfer learning opportunities and new training datasets.
- Build AI models from scratch and help product managers and stakeholders understand results.
- Create APIs and help business customers put the results of your AI models into operations.
- Finally, keep current on the latest AI research relevant to our business domain.
- Minimum four to five years of hands-on programming experience working on large enterprise products preferred.
- Demonstrated proficiency in multiple programming languages with a strong foundation in a statistical platform such as Python, R, SAS, or MatLab.
- Experience building AI models using Python or AI platforms such as Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI, IBM Watson, Keras, TensorFlow, or Theano.
- You have demonstrated commitment to learning about AI through your initiatives through courses, books, or side projects.
- Proven experience as a Data Scientist or Data Analyst
- Experience in data mining
- Understanding of machine-learning and operations research
- Experience using business intelligence tools (e.g., Tableau) and data frameworks (e.g., Hadoop)
- Analytical mind and business acumen
- Strong math skills (e.g., statistics, algebra)
- Problem-solving aptitude
- Excellent communication and presentation skills
- Able to translate complex outcome to layman understandable presentation in the platform
- BSc/BA in Computer Science, Engineering or relevant field; graduate degree in Data Science or relevant quantitative field is preferred
- Preferably, you have worked in a startup environment with large enterprise experience.
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