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Senior Data Specialist - R01571898 en Brillio-2

Brillio-2 · Pune, Indien · Hybrid

Python

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Description

Senior Data Specialist

Job requirements

Experience Range: With at least 5 years of hands-on experience in advanced data science, including statistical analysis and machine learning, and up to 8 years in related roles Key Responsibilities:
  • Design and implement advanced statistical models, including hypothesis testing, regression analysis, and classification algorithms, to drive business outcomes
  • Conduct rigorous statistical analysis using t-tests, z-tests, and probabilistic graph models to extract actionable insights from large datasets
  • Build, train, and deploy predictive models for forecasting and classification tasks using machine learning frameworks such as TensorFlow, PyTorch, and Sci-Kit Learn
  • Perform data cleaning, transformation, and exploratory analysis utilizing Python, PySpark, R, and statistical tools like SAS or SPSS
  • Apply time series forecasting methods, including exponential smoothing, ARIMA, and ARIMAX, to predict trends and inform strategic decisions
  • Develop and maintain data validation and monitoring pipelines to ensure data quality and model performance
  • Collaborate with cross-functional teams to translate business requirements into analytical solutions and communicate findings effectively
  • Automate machine learning workflows to streamline deployment and enhance scalability
    • Required Skills:
  • Expertise in hypothesis testing (t-test, z-test)
  • Advanced regression analysis (linear and logistic)
  • Programming proficiency in Python and PySpark
  • Hands-on experience with SAS or SPSS for statistical computing
  • Knowledge of probabilistic graph models
  • Experience with data validation frameworks such as Great Expectations
  • Time series forecasting techniques (exponential smoothing, ARIMA, ARIMAX)
  • Familiarity with classification algorithms (decision trees, SVM)
  • Experience with machine learning frameworks (TensorFlow, PyTorch, Sci-Kit Learn)
  • Proficiency in R for statistical modeling
    • Preferred Skills:
  • Experience with distance metrics (Hamming, Euclidean, Manhattan)
  • Expertise in model monitoring tools beyond Great Expectations, such as Evidently AI
  • Experience in deploying models using BentoML
  • Familiarity with orchestration tools for ML workflows, such as KubeFlow
  • Background in designing scalable machine learning pipelines
    • Desired Qualifications:
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
  • Certification in Data Science, Machine Learning, or Advanced Analytics (e.g., Microsoft Certified: Azure Data Scientist Associate, SAS Certified Data Scientist)
  • Certification in Python or R programming (e.g., PCEP, PCAP, R Programming Certification)
    • Additional Information: Immediate joiner required
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