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Data Architect - R01570398 en Brillio-2

Brillio-2 · Bangalore, Indien · Hybrid

Python

AWS

Cloud

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Description

Data Architect

Job requirements

Experience Range: With at least 7 to 10 years of experience in data architecture, data science, advanced statistical modeling, and AI architecture Key Responsibilities:
  • Design and architect robust data pipelines and frameworks to support advanced analytics, machine learning, and AI workloads
  • Develop and implement statistical and AI models, including regression (linear and logistic), classification algorithms, forecasting techniques (ARIMA, exponential smoothing), and deep learning architectures
  • Lead the integration of probabilistic graph models, advanced statistical tests (hypothesis testing, T-Test, Z-Test), and AI-driven solutions into production systems
  • Collaborate with data scientists and engineering teams to optimize data workflows and AI model deployment using tools such as KubeFlow and BentoML
  • Ensure data quality and integrity by implementing validation frameworks like Great Expectations and Evidently AI
  • Manage and optimize large-scale data processing and AI environments using Python, PySpark, R, and SAS/SPSS
  • Evaluate and select appropriate machine learning and AI frameworks (TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, MXNet) for scalable model deployment
  • Provide technical leadership in the adoption of emerging technologies and best practices in data architecture, advanced analytics, and AI solutions
    • Required Skills:
  • Advanced proficiency in Python and PySpark
  • Expertise in statistical analysis and computing
  • Hands-on experience with SAS and SPSS
  • Strong knowledge of hypothesis testing, T-Test, and Z-Test
  • Experience with regression techniques (linear and logistic)
  • Proficiency in probabilistic graph models
  • Familiarity with Great Expectations and Evidently AI for data validation
  • Forecasting expertise using ARIMA, ARIMAX, and exponential smoothing
  • Working knowledge of KubeFlow and BentoML
  • Experience with classification algorithms (Decision Trees, SVM)
  • Experience architecting AI solutions and deploying deep learning models
    • Preferred Skills:
  • Advanced experience with ML and AI frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
  • Expertise in distance metrics (Hamming, Euclidean, Manhattan)
  • Proficiency in R and R Studio
  • Experience with scalable AI model deployment in cloud environments
  • Knowledge of automated model monitoring, drift detection, and AI lifecycle management
    • Desired Qualifications:
  • Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, or a closely related discipline
  • Certification in Data Architecture, Data Science, or AI (e.g., Certified Data Professional, Microsoft Certified: Azure Data Scientist Associate, AI Architect certification)
  • Certification in Machine Learning frameworks or platforms (e.g., TensorFlow Developer Certificate, AWS Certified Machine Learning – Specialty)
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