✦Role summaryAI-generated
This role focuses on building Next Best Offer models and advanced data science solutions to enhance customer engagement at Brillio. Candidates will develop, validate, and deploy machine learning pipelines using Python, PySpark, R, and KubeFlow while applying statistical techniques and classification algorithms.
About this role
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 engagementApply statistical techniques such as hypothesis testing, t-tests, z-tests, and regression methods to extract actionable insights and support data-driven decision-makingBuild, validate, and optimize machine learning models using Python, PySpark, and R to ensure high accuracy and reliabilityLeverage probabilistic graph models and classification algorithms, including decision trees and support vector machines, to address complex business challengesOptimize and automate machine learning pipelines for scalable deployment using KubeFlow and BentoML, improving operational efficiencyConduct comprehensive statistical analysis with SAS, SPSS, and R Studio to inform business strategiesMonitor model performance using evaluation metrics and recommend data-driven improvements to maintain model effectivenessCollaborate with cross-functional teams to translate business requirements into impactful data science solutionsRequired Skills:
PythonPySparkSASSPSSRProbabilistic graph modelsRegression methods (linear and logistic)Forecasting methods (exponential smoothing, ARIMA, ARIMAX)TensorFlowPyTorchScikit-learnCNTKKerasMXNetDecision treesSupport Vector Machines (SVM)Distance metrics (Hamming, Euclidean, Manhattan)KubeFlowBentoMLPreferred Skills:
Experience with Great Expectations and Evidently AI for model validation and monitoringExpertise in deploying machine learning models in cloud-based environmentsKnowledge of advanced ensemble methods and boosting algorithmsFamiliarity with A/B testing and experimental designBackground in recommendation systems and personalization algorithmsDesired Qualifications:
Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a quantitative discipline relevant to data scienceCertification in Machine Learning or Data Science from a recognized institution such as Coursera, edX, or DataCampRelevant certification in statistical analysis or analytics, such as SAS Certified Statistical Business AnalystSimilar open roles
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