Data Scientist - R&D (AI/ML)

Vermeer CorporationAmes, IA
Hybrid

About The Position

Vermeer equips customers doing important work around the world. We are global, driven by innovation and growing. The equipment we make manages natural resources, connects people and feeds and fuels communities. We live out a caring culture, we demonstrate agility, we keep a focus on customers and are stewards of our resources. These beliefs drive our culture, determine how we treat others and steer our business. Are you the type of person who is passionate about data and deriving new insights from it? In this role you will research how different data streams can be used to inform new or improved products and processes. We’re looking for an experienced data scientist who thrives in a fast paced, hands-on team.

Requirements

  • Bachelor’s degree in Computer Science, Data Science, Mathematics, or other related field with three years of relevant experience; or equivalent combination of education and experience required.
  • Experience with machine learning operations, data modeling concepts, and data storage technologies, and how to extract from these sources using querying languages such as SQL and/or KQL.
  • Experience in translating insights into business language, enabling informed business decisions.
  • Experience with programming languages such as Python or R and tools such as Matlab.

Nice To Haves

  • Experience with Databricks, MLflow, Copilot Studio, Langchain, Ollama, large language models and RAG databases

Responsibilities

  • Develop and combine data models and apply machine learning algorithms to analyze large data sets to identify patterns and predict/forecast trends.
  • Identify valuable data sources and collaborate with data engineering teams to automate collection process, clean data, and pre-process for later use.
  • Apply non-linear regression modeling, simulations, or other statistical analysis techniques to uncover trends and correlations.
  • Use data visualization techniques and storytelling to present information and solutions to address business challenges.
  • Produce business insights through leading continuous discovery, stakeholder collaboration, and documentation to enhance data literacy.
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