Job Description
Join Omaha Innovations Group as a Senior Data Scientist and drive transformative insights for Fortune 500 clients. We're a rapidly growing analytics powerhouse with a passion for solving complex business challenges through data. Our collaborative culture combines cutting-edge technology with Midwest values, offering unparalleled career growth in a direct-hire role. Enjoy comprehensive benefits, flexible work arrangements, and the opportunity to work on high-impact projects that shape industries.
As a key member of our data science team, you'll leverage advanced statistical modeling and machine learning techniques to deliver actionable solutions. We invest heavily in professional development through conferences, certifications, and mentorship programs. Omaha's thriving tech scene, affordable living, and vibrant cultural attractions make it an ideal place to build your career.
Responsibilities
- Develop predictive models using Python, R, and SQL to optimize business KPIs
- Design and implement A/B tests for product optimization initiatives
- Create interactive dashboards using Tableau and Power BI for executive reporting
- Collaborate with cross-functional teams to translate data insights into actionable strategies
- Mentor junior data scientists and conduct peer code reviews
- Present findings to C-level stakeholders with compelling data visualizations
- Stay current with emerging ML techniques and implement industry best practices
Qualifications
- Master's degree in Data Science, Statistics, Computer Science, or related field
- 5+ years of experience in predictive modeling and machine learning
- Expert proficiency in Python (scikit-learn, TensorFlow) and SQL
- Strong background in statistical analysis and experimental design
- Experience with cloud platforms (AWS/GCP) and big data technologies
- Proven ability to communicate complex technical concepts to non-technical audiences
- Portfolio demonstrating successful data-driven projects
- Professional certifications (e.g., AWS Data Science, Google ML) preferred