: Data Scientist - Machine Learning
1 Kendall Square
Cambridge, MA 02139

Employee Testimonials

Inari Employee testimonial
Christopher Bagley Sr. Director HTP Design


About the role...

We are looking for a Data Scientist to join a growing machine learning team within our greater science organization. This team works closely with bioinformaticians, software engineers, and wet lab scientists to build predictive models that facilitate decision-making at both the science and product levels. This person would be a core developer of our deep learning toolkit focused primarily on protein engineering and discovery. The role will be based at the company headquarters in Cambridge, MA.

As a Data Scientist, you will

  • Be an early contributor to the young, but rapidly growing field of deep learning on biological sequences
  • Adapt industry-leading NLP model architectures to a new and data-rich domain, and develop new methods and benchmarks for validation.
  • Design and deploy generative models to enable machine-assisted novel protein discovery
  • Effectively utilize relevant public and proprietary databases to develop ML models to predict informative biophysical attributes, improve functionality, and design new proteins
  • Keep up to date with the latest in NLP and deep learning research in order to proactively identify, assess, and internalize promising methods and tools
  • Communicate and explain computational models and ML techniques to a broad scientific audience from diverse disciplines
  • Work closely with our software engineering team to enable scaling of approaches and access to data from our various labs and fields
  • Develop robust integrations with strategic third party tools, platforms and models
  • Contribute to design and overall engineering and science roadmap
  • Be a partner in our scientific projects: assist in the design and analysis of wet lab experiments

You bring 

  • A basic understanding of common bioinformatics tools and file formats or a strong interest to learn about them
  • 2+ years of analysis experience  
  • 1+ year of data science experience including working with neural networks
  • Extensive experience writing code and analysing data in Python
  • Experience with machine learning libraries like TensorFlow and/or PyTorch
  • Desire to work in a mission driven organization focused on sustainability and how we grow food
  • Interest in learning new technology or domains. We are an organization that spans many disciplines
  • A strong awareness of current deep learning literature and a willingness to test novel applications of these methods to biological data
  • Creative thinking, willingness to be bold and take risks
  • Openness to giving and receiving ideas, perspectives, and feedback across multiple teams

Bonus qualifications...

  • Previously worked with agricultural, DNAseq and RNAseq data, and discovery projects
  • Experience with container technologies: Docker and Kubernetes
  • Experience working with large data tooling: Beam, Spark, Hadoop
  • Experience with AWS tools: EC2, S3, Sagemaker
  • Knowledge of and enthusiasm for biophysics, biochemistry, and biotechnology

Employee Testimonials

Inari Employee testimonial
Karl Kremling
Data Scientist

I came to Inari because of the great opportunity in Cambridge to combine data science and the best molecular biology in the world.

Christopher Bagley Sr. Director HTP Design
Christopher Bagley
Sr. Director HTP Design

I am excited to have an impact on making those big fields even more productive.

Chris Bischke Inari Testimonial
Chris Bischke
Software Engineer

I never saw myself in agriculture, but when talking to the scientists here I could see the opportunity to help build computational platforms that supports a company mission that feeds the world. When I started interviewing I saw the potential for building new things at the intersection of engineering & data science -- that is what interested me most

Ruijuan Li Binformatics Scientist
Ruijuan Li
Binformatics Scientist

I joined Inari because on this team I feel I help feed the world.