Data Scientist

TarganRaleigh, NC
Onsite

About The Position

The Data Scientist is responsible for analyzing both commercial and R&D datasets to generate insights that drive the development of innovative solutions for the company. The Senior Data Scientist will actively communicate with stakeholders regarding the performance of production equipment and collaborate with the broader Data Science team to develop new tools that leverage our commercial data to create innovative products. They will serve as a key resource, driving R&D with a data-first approach across various disciplines, including engineering and biology.

Requirements

  • 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.
  • Bachelor’s Degree in Data Science, Statistics, Bioinformatics, Computational Biology or a related field.
  • 5-7 years of experience working in data science, or related field.

Nice To Haves

  • 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.

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.
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