Principal Data Scientist (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
TL;DR
Principal Data Scientist (AI): Designing and deploying advanced statistical and machine learning solutions for large-scale data analysis with an accent on predictive analytics and automated data pipelines. Focus on building probabilistic graph models, optimizing high-load pipelines using PySpark, and ensuring model reliability via rigorous evaluation frameworks.
Location: Remote (USA)
Company
is a global digital transformation services firm specializing in AI and data engineering to help clients drive measurable business impact.
What you will do
- Design and implement robust statistical models and ML algorithms for large-scale predictive analytics.
- Lead end-to-end data science projects, including hypothesis testing, regression analysis, classification, and forecasting.
- Optimize and automate data pipelines using Python, PySpark, and R to ensure efficient feature engineering.
- Develop, validate, and maintain probabilistic graph models and advanced statistical computing frameworks.
- Build, train, and deploy models using industry-leading frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn.
- Mentor and guide junior data scientists to foster technical excellence within the team.
Requirements
- 15-18 years of experience in advanced data science roles with extensive leadership in deploying ML solutions.
- Expertise in hypothesis testing (T-Test, Z-Test) and advanced regression techniques.
- Strong programming proficiency in Python, PySpark, and R/R Studio.
- Hands-on experience with SAS and SPSS for statistical computing.
- Experience with forecasting methods (ARIMA, ARIMAX) and classification algorithms (SVM, Decision Trees).
- Master’s or PhD degree in Data Science, Statistics, Computer Science, or Mathematics.
Nice to have
- Experience implementing advanced model monitoring with Evidently AI.
- Expertise in data pipeline orchestration using Kubeflow.
- Experience with large-scale distributed computing environments.
- Relevant certifications in machine learning or advanced statistical analysis.
Culture & Benefits
- Remote work arrangement.
- Commitment to equal employment opportunity and diversity.
- Environment focused on continuous learning and technical excellence.
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