Data Scientist to Data Scientist LeadJob Number: 167503
This position is open to a Data Scientist, Senior or Lead. As a claims data scientist
, you’ll use machine learning, engineering and languages like Python to develop tools, analyses and applications that solve complex business problems. Tackle wide-ranging problems with techniques you may need to research, learn and create. Your final products can range from design of predictive models to sophisticated visualizations or decision-support tools delivered through user-facing web apps you develop.Must-have qualifications
- Bachelor's degree or higher with quantitative focus in Data Science, Econometrics, Statistics, Operations Research, Computer Science or related field (e.g. Mathematics).
- In lieu of a degree, a minimum of 3 years of relevant experience in statistical/quantitative modeling and/or machine learning tools and in using various database tools processing large volumes of structured and unstructured data.
- Proficiency in SQL and one higher level programming language (i.e. Python or R)
- Excel in communicating technical findings to a wide range of audiences
- Experience with tools like Hadoop, AWS, and Linux
- Experience developing web applications using popular frameworks (i.e. Flask, Node.JS, Angular and Bootstrap)
- Experience with GIT version control system
Sponsorship for work authorization for this position is available for candidates who already possess an H-1B visa.
- Gainshare bonus from 30% to 40% of your eligible earnings; Progressive rewards each of us with an annual bonus based on company performance
- 401(k) with dollar-for-dollar company match up to 6%
- Diverse, inclusive and welcoming culture with Employee Resource Groups
- Career development and tuition assistance
- Onsite gym and healthcare at large locations
- Wellness programs to help you maintain a better quality of life
- Medical, dental and vision, including free preventive care
Equal Opportunity EmployerJob:
Business AnalysisPrimary Location:
United States-Ohio-Mayfield HeightsSchedule: