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Top Senior Data Science Jobs in Houston, TX
Big Data • Analytics • Business Intelligence • Big Data Analytics
Design, develop, and deploy time-series and machine-learning forecasting models (ARIMA, SARIMA, ETS, XGBoost, LightGBM) for demand planning, inventory, and sales forecasting. Perform large-scale SQL data processing, operationalize models in cloud environments (Azure preferred), present insights, and lead client workshops.
Top Skills:
ArimaAzureCloudEtsGbmLightgbmNumpyPandasPythonRandom ForestSarimaScikit-LearnSQLStatsmodelsXgboost
Information Technology • Consulting
Design, build, validate, deploy, and monitor machine learning and generative AI solutions for healthcare and life sciences. Work with EHR, claims, and registry data to produce clinical predictions, operational optimizations, and LLM-powered applications. Translate results for stakeholders, document best practices, and mentor client teams.
Top Skills:
Aws SagemakerAzure MlBigQueryCi/Cd For MlData FactoryDatabricksEmbeddingsFhirFine-TuningGcp Vertex AiHl7Llm ApisLlm Evaluation FrameworksLookerMlflowNumpyPandasPower BIPrompt EngineeringPythonRag PipelinesRedshiftS3Scikit-LearnSnowflakeSQLSynapseTableauVector Databases
Healthtech • Software
As a Senior Data Scientist, you'll lead projects leveraging data to enhance healthcare outcomes, mentor team members, and align data efforts with business goals.
Top Skills:
Machine Learning ToolsPythonSQLStatistical Packages
Big Data • Analytics • Business Intelligence • Big Data Analytics
The Lead Data Scientist will design, develop, and deploy GenAI solutions, mentor teams, and translate business needs into analytical solutions. Responsibilities include developing end-to-end ML pipelines, presenting solutions to stakeholders, and ensuring efficient delivery of analytics solutions.
Top Skills:
Azure OpenaiLanggraphMlflowPythonSQL
eCommerce • Information Technology • Machine Learning • Marketing Tech • Database • Analytics • Big Data Analytics
Lead development and operationalization of measurement products (MMM, incrementality, insights, recommendations). Build, deploy, and maintain production-grade statistical and ML systems, debug end-to-end data and model issues, evaluate methodologies, and partner with engineering, product, and customer teams to improve measurement accuracy and reliability. Provide customer-facing explanations and support for measurement outputs.
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