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About the Role
The Data Scientist is responsible for analyzing commercial and R&D datasets to generate insights that drive the development of innovative solutions. This role involves communicating production equipment performance, developing new tools with commercial data, and driving R&D with a data-first approach across engineering and biology.
Responsibilities
- Analyze and interpret complex biological data sets to generate actionable insights.
- Develop and implement machine learning models to enhance data analysis and tool development.
- Integrate commercial data with biological data to identify patterns and opportunities for product development.
- Collaborate with cross-functional teams including bioinformatics, software engineering, and product development to build proprietary tools.
- Drive the development of new products by leveraging commercial data to meet market needs and company objectives.
- Ensure the quality and accuracy of data and analyses through rigorous testing and validation processes.
- Stay current with the latest advancements in data science, bioinformatics, and related fields to continuously improve methodologies and approaches.
- Mentor junior software developers and provide guidance on best practices and advanced analytical techniques.
- Communicate complex data insights and recommendations to non-technical stakeholders effectively.
Requirements
- Experience in a commercial or industrial setting, particularly biotechnology preferred.
- Experience working with biological data preferred.
- Experience with computer vision preferred.
- Knowledge of regulatory requirements and data privacy considerations in handling biological and commercial data preferred.
- Ability to work in a fast-paced environment and adapt to changing priorities preferred.
Skills
- Proficiency in Python and/or R for data analysis, visualization, and machine learning.
- Experience in visualization/report generation using Python/R libraries such as Plotly, Shiny, etc.
- Proficiency in SQL and experience with database management systems (e.g., MongoDB, SQL Server).
- Experience working with cloud platforms such as Azure for data storage, processing, and analysis.
- Solid understanding of machine learning algorithms and statistical analysis.
- Familiarity with deep learning frameworks, such as TensorFlow and PyTorch.
- Excellent problem-solving skills and ability to think critically and creatively.
- Excellent communication skills, both written and verbal.
Location
- Office environment
- Flex space building
- Laboratory
- Machine shop
- Manufacturing floor
- Warehouse space
Work Type
- Onsite
Experience Level
- 5-7 years of experience working in data science, or related field.
Education Level
- Bachelor’s Degree in Data Science, Statistics, Bioinformatics, Computational Biology or a related field.
About the Company
- Work is performed inside a flex space building consisting of offices, open desk space, laboratory, machine shop, and a manufacturing floor.
- Level of noise is usually quiet in the office environment and temperature controlled.
- Noise levels are elevated in the warehouse space where temperatures can vary depending on the outside elements and weather.
- Travel may be required, including up to 2-8 trips per year to visit suppliers, attend conferences, meetings (customer, investor, and business) and customer sites (hatcheries).