1 день назад
Data Scientist (Machine Learning)
110 000 - 151 250$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Data Scientist (Machine Learning): Developing predictive models and data-driven business solutions for insurance and financial services with an accent on statistical analysis, machine learning, and actionable business insights. Focus on mining and transforming raw data, validating supervised and unsupervised models, and building forecasting and optimization algorithms.
Location: Bloomington, Illinois; onsite
Base pay: $110,000–$151,250 per year, plus eligibility for a short-term incentive plan.
Company
provides personal and business insurance products, retirement services, and investment services to nearly one million households.
What you will do
- Work with business stakeholders to define problems that can be addressed through analytics.
- Develop business cases for analytical opportunities and provide quantitative recommendations.
- Mine and transform raw data into actionable business information.
- Develop predictive models and advanced algorithms using statistical and machine learning techniques.
- Validate model performance with appropriate standards and error metrics.
- Develop supervised and unsupervised machine learning, forecasting, and optimization solutions while maintaining data version control and documentation.
Requirements
- Typically 7 or more years of relevant experience, or an equivalent combination of experience, education, and training.
- Experience applying statistical methods to complex business problems.
- Experience with predictive modeling, machine learning, data mining, forecasting, and optimization.
- Ability to analyze business data and communicate insights and recommendations.
Culture & Benefits
- Medical, dental, vision, disability, and life insurance benefits.
- 401(k) plan with company match.
- Opportunities for learning, career growth, and movement across areas of the business.
- Collaborative work focused on supporting clients and local communities.
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