The Senior Data Science Engineer position is responsible for applying machine learning, data visualization, and other data science techniques to explore and create data-driven solutions to the problems and opportunities of Inmar’s business units, working closely with application engineering teams to bring those solutions to production. This role provides thought leadership on new products and solutions and identifies viable solutions through applied research.
Major Responsibilities/Essential Functions:
Use data science techniques and tools to explore and create solutions
Identify, extract, clean, and transform data
Work with business units and others to understand the problem space and challenges
Work with application engineering teams to bring solutions to production
Publicize results and findings via reports, presentations, and technical specifications
Keep skills and knowledge up-to-date
Education:
Required: Bachelor’s degree in Computer Science, Statistics, or any field with an applied quantitative and experimentation focus
Preferred: Masters or PhD in a quantitative and experimentation focused field
Required Qualifications:
Extensive experience with machine learning, data visualization, and other data science techniques using Python, R, Scala, or other languages
In-depth experience with database systems, both SQL and NoSQL, including Hadoop-based systems
In-depth experience with software development (scripting, programming, versioning, testing, deploying, etc.) on Linux and Microsoft platforms
In-depth experience with data processing, extraction, cleansing, and transformation
Experienced at preparing reports and giving presentations for technical and non-technical audiences
Self-directed and curious, but must be able to function well as part of a team
Good understanding of the scientific method
Constant learner
Preferred Qualifications:
Experience with the SCRUM/Agile process
Experience with Tableau or other data visualization dashboard tools
Experience with Ansible and other deployment automation tools
Experience with cloud-based platforms, such as Azure
