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Brillio

Turning technological disruptions into the advantages. Let's create something Brillian(t) together!

Principal Data Scientist

Data ScientistData ScientistFull TimeRemoteLeadTeam 1,001-5,000H1B SponsorCompany SiteLinkedIn

Location

New Jersey

Posted

3 days ago

Salary

$185K - $190K / year

Seniority

Lead

Postgraduate Degree15 yrs expEnglishKerasPySparkPythonPyTorchTensorflow

Job Description

Principal Data Scientist

Brillio

• Design and implement robust statistical models and machine learning algorithms for large-scale data analysis and predictive analytics • Lead end-to-end development of data science projects, including hypothesis testing, regression analysis, classification, and forecasting • Collaborate with cross-functional teams to define business requirements, translate them into analytical solutions, and drive measurable impact • Optimize and automate data pipelines using Python, PySpark, and R, ensuring efficient data processing and feature engineering • Develop, validate, and maintain probabilistic graph models and advanced statistical computing frameworks • Utilize industry-leading ML frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn to build, train, and deploy models • Establish rigorous model evaluation and monitoring processes using tools like Great Expectations and Evidently AI • Mentor and guide junior data scientists, fostering technical excellence and continuous learning within the team

Job Requirements

  • 15 - 18 years of experience in advanced data science roles, with extensive leadership in designing and deploying statistical and machine learning solutions
  • Expertise in hypothesis testing, including T-Test and Z-Test methodologies
  • Advanced proficiency in regression techniques (linear and logistic)
  • Strong programming skills in Python, PySpark, and R/R Studio
  • Hands-on experience with SAS and SPSS for statistical analysis and computing
  • In-depth knowledge of probabilistic graph models
  • Experience with forecasting methods such as Exponential Smoothing, ARIMA, and ARIMAX
  • Practical use of classification algorithms including Decision Trees and Support Vector Machines (SVM)
  • Proficiency with ML frameworks: TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet
  • Familiarity with distance metrics (Hamming, Euclidean, Manhattan)
  • Working knowledge of Kubeflow and BentoML for model deployment and orchestration
  • Master’s or PhD degree in Data Science, Statistics, Computer Science, Mathematics, or a related field
  • Relevant certifications in machine learning, statistical analysis, or advanced data science

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