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Principal Data Scientist - R01568403

5 days, 10 hours ago
United States
Lead
Data Scientist
Data Science and Analytics
Apache Spark Feature Engineering Keras Kubeflow Machine Learning Python PyTorch R Scikit-learn TensorFlow
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Brillio

Brillio

Brillio is a global leader in Enterprise Digital Transformation Solutions, partnering with companies to drive business improvement and competitiveness through innovative technology solutions.

IT Services
1001-5000
Founded 2014
View All Jobs 16

Description

  • Design and implement statistical models and machine learning algorithms for large-scale analytics and predictive use cases.
  • Lead end-to-end data science projects spanning hypothesis testing, regression, classification, and forecasting.
  • Partner with cross-functional teams to translate business requirements into analytical solutions.
  • Optimize and automate data pipelines, processing, and feature engineering using Python, PySpark, and R.
  • Develop, validate, and maintain probabilistic graph models and statistical computing frameworks.
  • Build, train, and deploy models using frameworks including TensorFlow, PyTorch, and Scikit-learn.
  • Establish model evaluation and monitoring processes using tools such as Great Expectations and Evidently AI.
  • Mentor junior data scientists and promote technical excellence across the team.

Requirements

  • 15–18 years of experience in advanced data science roles, including leadership designing and deploying statistical and machine learning solutions.
  • Master’s or PhD in Data Science, Statistics, Computer Science, Mathematics, or a related field.
  • Expertise in hypothesis testing, including t-tests and z-tests, and linear and logistic regression.
  • Strong programming skills in Python, PySpark, R, and RStudio.
  • Hands-on experience with SAS and SPSS for statistical analysis and computing.
  • Knowledge of probabilistic graph models, forecasting methods including Exponential Smoothing, ARIMA, and ARIMAX, and classification algorithms such as decision trees and SVMs.
  • Proficiency with TensorFlow, PyTorch, Scikit-learn, CNTK, Keras, and MXNet.
  • Working knowledge of Kubeflow and BentoML for model deployment and orchestration.
  • Experience with advanced monitoring using Evidently AI, distributed computing environments, and statistical validation and reproducibility practices preferred.
  • Relevant machine learning, statistical analysis, or advanced data science certifications preferred.

Interested in this position?

Apply directly on the company website

Apply Now

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