Position Summary
As a Data Scientist, you will be supporting the Data Science group and actively participating in all the processes of a data science project, including exploratory data analysis, feature generation and selection, model creation, and model optimization to boost performance and accuracy. It is important that the person in this role is proactive and independent. You should be a problem solver with an open mind and an eagerness to pick up new skills ranging from deeper statistical analysis and better modeling skills to honing programming and communication skills.
Responsibilities
- Apply data science practices on your specific assigned workstreams; particularly:
- Perform exploratory data analysis to understand relationships and opportunities to influence outcomes
- Select appropriate machine learning models for tasks, and building and training working versions of those models using Python and other open-source tools
- Score and explain the performance of models applied to data
- Develop and document proofs of concept to verify ideas
- Collaborate daily with Data Science Managers and Data Scientists to receive guidance and feedback on your work to develop your skills and ensure alignment with workstream objectives
- Be a contributor to the planning and direction of a project and effectively prioritize your tasks and objectives
- Contribute to internal discussions on emerging machine learning methodologies
Qualifications
Required:
- Undergraduate degree in a quantitative field (computer science, engineering, mathematics, physics, machine learning, statistics)
- Experience using Python and relevant libraries (NumPy, Pandas, Scikit-learn, etc.)
- Coursework related to machine learning, NLP, deep learning, and programming
- Hands-on application experience using common machine learning (atleast 1 project) libraries and techniques, including TensorFlow, PyTorch, and big data platforms
- Demonstrated ability to write high-quality code
- Demonstrated ability to develop machine learning models
Preferred:
- Master’s degree in a quantitative field (computer science, engineering, mathematics, physics, machine learning, statistics)
- Data Bricks
- Relevant work experience (internships, school jobs, etc.)
- Familiarity with the Microsoft Azure cloud-based ecosystem, including Azure DevOps
- Familiarity with machine learning model development life cycles
- Experience with version control practices and tools (Git, etc.)
- Public AI-related projects you have developed available on GitHub