Data Scientist

**Your Journey at Crowe Starts Here**:
At Crowe, you have the opportunity to deliver innovative solutions to today’s complex business issues. Crowe’s accounting, consulting, and technology personnel are widely recognized for their in-depth expertise and understanding of sophisticated process frameworks and enabling technologies, along with their commitment to delivering measurable results that help clients build business value. Our focus on emerging technology solutions along with our commitment to internal career growth and exceptional client value has resulted in a firm that is routinely recognized as a “Best Place to Work.” We are 75 years strong and still growing. Come grow with us

**About Crowe Data Science**

Everything we do is about making the future of human work more purposeful. We do this by leveraging state-of-the-art machine learning, modern architectures, and industry experts, to create AI-powered software-as-a-service.

Our world-class Data Science professionals give Crowe the ability to capture and harness the power of data. A combination of data scientists and machine learning engineers create and deploy AI functionality into software to solve complex problems. This type of group, rarely seen anywhere except large tech companies, focuses on building scalable AI products, not just one-time insights. You will learn and build on a wide range of technologies - distinguishing Crowe in the market and driving the firm’s technology and innovation strategy.

The future is powered by AI, come build it with us.

**About the Team**
- ** We believe machine learning is software.** While we know our way around Jupyter notebooks and ggplot2, they are not the end of our machine learning pipelines. Our team uses modern frameworks and tools (git, Docker, Kubernetes) to engineer machine learning solutions.
- ** We foster good science.** You are given the time and resources you need to build your expertise in your project, and you will guide fellow data scientists, software engineers, and other Crowe staff through your work.
- ** We want to make good scientists better.** Data scientists have plenty of options on the job market. We want to be one of the best ones. We have a journal club that meets weekly, regular opportunities for team members to teach each other, support for conferences, and recurring reading groups. Moreover, our team offers generous PTO, a flexible work from home policy, and a strong commitment to work-life balance.

**About the Role**
- We work on medium-term machine learning projects (1-6 months) with a high degree of autonomy.
- In order to further the Data Science Team strategic imperative of having a “Culture of reuse: tools, products, and processes.”, the primary strategy of the Toolkit Team will be to develop generalizable tools for common problems and facilitate the sharing of code within/between projects.
- Work within the Data Science Team to define common problems and identify opportunities in the existing codebase to solve current and future problems
- Research, prototype, and validate data science / machine learning approaches to address common requirements for our machine learning products
- Collaborate with software engineers to get your machine learning models from prototype to production
- Champion the use and adoption of Toolkit libraries and services

**Required Skills**:

- ** Programming experience.** Your job will require you to code. We mainly write in Python, so experience in this language is preferred. Within the Python ecosystem, we learn and use a wide array of tools and frameworks. Familiarity with or a drive to learn common data science and machine learning libraries is a plus.
- ** Machine learning experience.** You enjoy machine learning. You've gone deeper than reading blog posts, ideally having several example machine learning projects from industry, academia, or personal settings that you can speak to.
- ** Capacity for autonomy.** You won’t be on your own on day one, but you will need the capacity to manage your time between research and tool development.
- ** Strong communication skills.** You are comfortable adjusting how you discuss machine learning projects, from the technical details to high-level concepts, depending on your audience of data scientist teammates, software engineer collaborators, and non-technical business stakeholders.
- ** Adaptable.** Toolkit problems will involve different areas of computer science and machine learning skills, sometimes within the same problem. You can context shift depending on the problem and can adjust if new problems and/or requirements arise requiring rethinking the approach to solving a problem.
- ** Detail oriented.** Toolkit is focused on making tools that just work. You like to find edge cases and potential bugs in code, you go above and beyond developing use cases beyond the requested basics, and you are meticulous with documenting code.

**Skills to Stand Out**
- ** Hackiness.** You like t