Data Scientist II
Simplot Company
Location
🇺🇸 Boise, United States
Type
full_time
Salary
Undisclosed
Posted
3w ago
Job Description
The Simplot Company is a diverse, privately held global food and agriculture company headquartered in Boise, Idaho. We are a true farm-to-table company with an integrated portfolio including food processing and food brands, phosphate mining, fertilizer manufacturing, farming, ranching and cattle production, and other enterprises related to agriculture. Summary As a Data Scientist with Simplot, you will leverage your expertise in statistics, machine learning and AI to develop solutions that solve complex business and operational problems. You will contribute to diverse and challenging projects, derive and communicate meaningful insights to business partners, and develop and deploy automated solutions to create business value across a variety of domains. In this role, you will have the opportunity to collaborate with other highly skilled data scientists, play a creative role on project teams, participate in high priority cross-functional initiatives, and grow and develop your own skillset through your work. Your curiosity, expertise and integrity will be instrumental in representing our team in engagements with our partners and stakeholders across the company, and in advancing Simplot’s utilization and development of industry-leading innovations in advanced analytics and AI. This role is full-time onsite at Simplot Headquarters in Boise, ID.
Key Responsibilities
- Participate as a member of a data science team.
- Apply technical knowledge to interpret business questions and
requirements
. • Work independently and in groups to resolve highly complex technical issues within a given technical area. • Partner with team members across IT and various business domainsm as appropriate. • Identify potential design, implementation or solution support risks and proactively alert management and technical leads. • Brainstorm, evaluate and implement solutions to both current and anticipated future business problems Typical