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Senior Data Science Lead - R01571251

Brillio
Posted 1 hour ago
IndiaHybridData & Analytics
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Senior Data Science Lead

Job requirements

Experience Range: With at least 8 years of experience in data science and advanced analytics, including recent leadership roles spanning up to 12 years Key Responsibilities:
  • Lead the design, development, and implementation of advanced statistical models and machine learning solutions to address complex business challenges and deliver measurable impact
  • Drive end-to-end data science project lifecycles, overseeing data exploration, hypothesis testing, feature engineering, model selection, and validation
  • Apply regression, classification, and forecasting techniques such as ARIMA, ARIMAX, exponential smoothing, and decision trees to generate predictive analytics and actionable insights
  • Collaborate with cross-functional teams to translate business objectives into actionable data science strategies and ensure alignment with organizational goals
  • Build, evaluate, and deploy scalable machine learning models using Python, PySpark, R, TensorFlow, PyTorch, and Sci-Kit Learn
  • Monitor data quality, bias detection, and model performance using Great Expectations and Evidently AI, ensuring robust analytics outcomes
  • Mentor and guide junior data scientists, providing technical leadership, conducting code reviews, and promoting best practices in statistical analysis and machine learning
  • Present findings and insights to stakeholders through clear visualizations and presentations, facilitating data-driven decision making
    • Required Skills:
  • Advanced proficiency in Python and PySpark for data processing and modeling
  • Expertise in statistical analysis, including hypothesis testing, t-tests, and z-tests
  • Strong knowledge of regression techniques (linear, logistic) and classification algorithms (decision trees, SVM)
  • Hands-on experience with probabilistic graphical models for complex data relationships
  • Proficiency with machine learning frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNet
  • Experience with forecasting methods including exponential smoothing, ARIMA, and ARIMAX
  • Competence in data quality and monitoring tools such as Great Expectations and Evidently AI
  • Working knowledge of SAS or SPSS for statistical analysis and computing
  • Familiarity with R and R Studio for advanced analytics
  • Understanding of distance metrics such as Hamming, Euclidean, and Manhattan
    • Preferred Skills:
  • Experience deploying machine learning models in production environments using KubeFlow or BentoML
  • Expertise in developing scalable data pipelines for machine learning workflows
  • Knowledge of advanced feature engineering and dimensionality reduction techniques such as PCA and t-SNE
  • Background in model interpretability and explainable AI methodologies (e.g., SHAP, LIME)
  • Exposure to real-time analytics and streaming data platforms such as Apache Kafka or Spark Streaming
    • Desired Qualifications:
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related discipline
  • Microsoft Certified: Azure Data Scientist Associate or TensorFlow Developer Certificate (preferred)
  • Formal training or certification in advanced statistical analysis or machine learning frameworks

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