Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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$88к-121к/год
$100к$130кмедиана$150к
По похожим ролям (48) ~ $130к/год
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Понятные задачи по моделированию в крупной аналитической компании дают хороший старт, но частая работа в офисе ограничивает гибкость.
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Текст:
Hirify AI/Оригинал
TL;DR
Analytic Scientist I (AI): Developing FICO Scores, exploratory analyses, and predictive models for credit-risk and business problems with an accent on large-scale data preparation, statistical analysis, and decisioning techniques. Focus on identifying patterns, engineering variables, selecting modeling criteria, and explaining analytical results to technical and non-technical stakeholders.
Location: Novato, CA, United States; hybrid role with onsite work required at the Novato office at least 3.5 days per week, with the remaining time eligible to be worked remotely.
Targeted base pay range: $88,000–$121,000 annually.
Company
hirify.global is a global analytics software company developing decisioning, credit-scoring, fraud-detection, and lending solutions for businesses and consumers in more than 100 countries.
What you will do
Develop and enhance hirify.global Scores using current data and decisioning techniques.
Design exploratory analyses and predictive models for business problems.
Assess historical data, clean datasets, identify patterns, create variables, define sampling and performance criteria, and select variables.
Support products through analytic investigations for internal teams and clients and through analytic content for sales and client materials.
Document methods and results and explain them clearly to technical and non-technical colleagues.
Requirements
Bachelor’s degree in Computer Science, Data Science, Engineering, Physics, Statistics, Mathematics, Operations Research, or another quantitative science field.
Hands-on academic or industry experience building predictive models on real-world data, including data cleaning and statistical analysis of large datasets.
Experience analyzing large datasets and applying data-cleaning and statistical-analysis techniques.
Exposure to financial services or credit data, or a similar relevant industry.
Proficiency in one or more of R, Perl, Python, SAS, SQL, Java, C, or C++, plus familiarity with basic software design principles and coding standards or best practices.
Knowledge or exposure to clustering, classification and regression trees, random forests, gradient boosting, time-series analysis, Bayesian networks, PCA, independent component analysis, linear and logistic regression, inference, estimation, experimental design, neural networks, or SVM.
Intellectual curiosity, motivation, self-direction, and the ability to learn new concepts quickly and adapt in a fast-paced environment.
Culture & Benefits
Inclusive culture centered on ownership, customer focus, and earning the respect of others.
Professional development through learning experiences and opportunities to leverage individual strengths.
Competitive compensation, benefits, and rewards programs.
People-first work environment with work/life balance, employee resource groups, and social events.
Hybrid work arrangement with the remaining work time eligible to be performed remotely after the required onsite schedule.
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