B
Brillio
Data Scientist

Data Scientist - R01570830

On-siteMidData Scientistposted 1mo ago
✦Role summaryAI-generated

This role focuses on building Next Best Offer models and advanced data science solutions to enhance customer engagement at Brillio. Candidates will develop, validate, and deploy machine learning pipelines using Python, PySpark, R, and KubeFlow while applying statistical techniques and classification algorithms.

Skills required

About this role

Data Scientist

Job requirements

Experience Range: With 4 to 6 years of experience in advanced data science roles, including hands-on involvement in machine learning and statistical modeling projects Key Responsibilities:

  • Develop and implement Next Best Offer models and advanced data science solutions to drive business objectives and enhance customer engagement
  • Apply statistical techniques such as hypothesis testing, t-tests, z-tests, and regression methods to extract actionable insights and support data-driven decision-making
  • Build, validate, and optimize machine learning models using Python, PySpark, and R to ensure high accuracy and reliability
  • Leverage probabilistic graph models and classification algorithms, including decision trees and support vector machines, to address complex business challenges
  • Optimize and automate machine learning pipelines for scalable deployment using KubeFlow and BentoML, improving operational efficiency
  • Conduct comprehensive statistical analysis with SAS, SPSS, and R Studio to inform business strategies
  • Monitor model performance using evaluation metrics and recommend data-driven improvements to maintain model effectiveness
  • Collaborate with cross-functional teams to translate business requirements into impactful data science solutions
  • Required Skills:

  • Python
  • PySpark
  • SAS
  • SPSS
  • R
  • Probabilistic graph models
  • Regression methods (linear and logistic)
  • Forecasting methods (exponential smoothing, ARIMA, ARIMAX)
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • CNTK
  • Keras
  • MXNet
  • Decision trees
  • Support Vector Machines (SVM)
  • Distance metrics (Hamming, Euclidean, Manhattan)
  • KubeFlow
  • BentoML
  • Preferred Skills:

  • Experience with Great Expectations and Evidently AI for model validation and monitoring
  • Expertise in deploying machine learning models in cloud-based environments
  • Knowledge of advanced ensemble methods and boosting algorithms
  • Familiarity with A/B testing and experimental design
  • Background in recommendation systems and personalization algorithms
  • Desired Qualifications:

  • Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a quantitative discipline relevant to data science
  • Certification in Machine Learning or Data Science from a recognized institution such as Coursera, edX, or DataCamp
  • Relevant certification in statistical analysis or analytics, such as SAS Certified Statistical Business Analyst
  • ✕ position closed

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