Data Scientist (Machine Learning/AI) at 1848 Ventures

1848 Ventures opportunities can be 100% remote or onsite in our office in Westfield Center, OH. Relocation assistance is available.

The Opportunity

The Venture Data Scientist leads efforts to identify, gather, and analyze data sets, surveys, and patterns to refine and validate innovation opportunities, as well as generate and test data-centric solution concepts. (It’s a mouthful, but trust us, it’s fun.)

In addition, as a core member of the Venture Development team, the Data Scientist will develop machine-learning prototypes, design automated processes to cleanse large data sets, and generate meaningful insights in support of the creation, validation, and launch of these solutions.

Curious? Here are the details you need to know.

What It Takes:

  • This is a multi-faceted role, one that requires significant thought-leadership and execution support from ideation through product development and launch. You’ll wear several hats:
  • Builder of smart solutions that improves business operations by combining data science and AI practices with human-centered design techniques.
  • Collaborator and hands-on consultant that bridges the gap between creative design and quantitative analysis, as well as between 1848 Ventures team members and external partners.

What You Need For This Role:

This is a unique opportunity to establish the technical direction for data science from the ground up, to choose the tools and tech that form the basis of our innovation process. In this role, you’ll leverage your collective work experience and education to:

  • Lead data and AI methods to drive innovation and/ or generate business value.
  • Engage in and lead diverse teams of internal employees and external partners.
  • Work as a high performer, execute with speed and agility, and apply creativity to work.
  • Identify and analyze exploratory data sets, craft surveys and evaluate responses, and prototype intelligent system maps as part of early-stage opportunity analysis, concept development, and concept refinement.
  • Use human-centered design to discover innovation opportunities and create data-driven solutions.
  • Design data-driven experiments to validate assumptions and build compelling features.
  • Create a data-collection strategy for predictive modeling and automated product improvements.
  • Oversee technical documentation; outline assumptions, approaches, and solutions and define high-value data insights to inform the team’s decision-making.
  • Keep the team informed on relevant data science topics and grow your own knowledge of machine learning, including prototyping new methods and tools; stay up-to-date on data privacy regulations and methodologies.

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