À propos de ce poste Senior Data Science Lead - R01571251 chez Brillio
Brillio · Hybride · Bangalore, Karnataka, India
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 impactDrive end-to-end data science project lifecycles, overseeing data exploration, hypothesis testing, feature engineering, model selection, and validationApply regression, classification, and forecasting techniques such as ARIMA, ARIMAX, exponential smoothing, and decision trees to generate predictive analytics and actionable insightsCollaborate with cross-functional teams to translate business objectives into actionable data science strategies and ensure alignment with organizational goalsBuild, evaluate, and deploy scalable machine learning models using Python, PySpark, R, TensorFlow, PyTorch, and Sci-Kit LearnMonitor data quality, bias detection, and model performance using Great Expectations and Evidently AI, ensuring robust analytics outcomesMentor and guide junior data scientists, providing technical leadership, conducting code reviews, and promoting best practices in statistical analysis and machine learningPresent findings and insights to stakeholders through clear visualizations and presentations, facilitating data-driven decision makingRequired Skills:
Advanced proficiency in Python and PySpark for data processing and modelingExpertise in statistical analysis, including hypothesis testing, t-tests, and z-testsStrong knowledge of regression techniques (linear, logistic) and classification algorithms (decision trees, SVM)Hands-on experience with probabilistic graphical models for complex data relationshipsProficiency with machine learning frameworks such as TensorFlow, PyTorch, Sci-Kit Learn, CNTK, Keras, and MXNetExperience with forecasting methods including exponential smoothing, ARIMA, and ARIMAXCompetence in data quality and monitoring tools such as Great Expectations and Evidently AIWorking knowledge of SAS or SPSS for statistical analysis and computingFamiliarity with R and R Studio for advanced analyticsUnderstanding of distance metrics such as Hamming, Euclidean, and ManhattanPreferred Skills:
Experience deploying machine learning models in production environments using KubeFlow or BentoMLExpertise in developing scalable data pipelines for machine learning workflowsKnowledge of advanced feature engineering and dimensionality reduction techniques such as PCA and t-SNEBackground 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 StreamingDesired Qualifications:
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a closely related disciplineMicrosoft Certified: Azure Data Scientist Associate or TensorFlow Developer Certificate (preferred)Formal training or certification in advanced statistical analysis or machine learning frameworks
