Senior Machine Learning Engineer
Strella
Job Description
The Strella Mission
\nMore than 40% of all fresh produce is wasted in the US, which accounts for over 17 billion dollars in lost product annually and contributes more carbon dioxide emissions than all of US transportation combined. Globally, food that is never consumed accounts for 7% of the global freshwater supply and 308MM hectares of land. Our goal is to reduce these drastic numbers by making the produce supply chain smarter through data-driven decisions.
\n \nStrella uses proprietary sensors to predict shelf life in the food supply chain. We use this information to reduce food waste and help deliver better quality produce to consumers. We have been commercialized for 5 years and are currently in our growth stage.
\n \nRole
\nWe are looking for an ambitious data scientist with 5+ years of experience to help us build the next generation of our modeling and prediction engine. The applicant must have a strong focus on delivering action-based results that can help customers make better decisions using data. Experience in agriculture is a plus.
\n \nAs a startup, we seek applicants who are self-starters and can wear multiple hats. We are in a rapid growth stage and are looking for people who thrive in a fast-paced environment while maintaining quality. This is an in-person role in either our Seattle or Wenatchee WA office.
\n \nResponsibilities
\n- \n
- Partner with developers, product managers, and business partners to frame problems mathematically and in the right business context \n
- Perform exploratory data analysis to gain a deeper understanding of the problem \n
- Construct and fit statistical, machine learning, or vision models \n
- Implement advanced analytics techniques to identify key factors impacting the quality and shelf life of fruits \n
- Develop predictive models and machine-learning algorithms to predict the shelf life of different types of fruits \n
- Design experimentation strategies for evaluating our models \n
- Collaborate with developers to implement algorithms in production \n
- Analyze experimental and observational data; communicate findings; facilitate launch decisions \n
Skills
\n- \n
- Bachelors, M.S. or Ph.D. in Machine Learning, Statistics, Operations Research, Optimization, Computer Science, or other quantitative fields or related work experience \n
- 5+ years of professional experience, startup experience required \n
- Proficiency in machine learning and experimentation. Experience with computer vision is a plus \n
- Proficiency with Python and working in a production coding environment \n
- Passion for solving unstructured and non-standard mathematical problems \n
- End-to-end experience with data, including querying, aggregation, analysis, and visualization \n
- Strong oral and written communication skills, and ability to collaborate and communicate with others to solve a problem \n
Benefits
\n- \n
- 401k matching \n
- Health & Dental \n
- Unlimited PTO \n
Salary Range: 145k - 170k
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