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Data Scientist - R01570830 en Brillio-2

Brillio-2 · Bangalore, Indien · Hybrid

Python

Business Analyst

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Description

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
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