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You will be updated with latest job alerts via emailKey Responsibilities:
Required Skills & Qualifications:
Develop and optimize machine learning models focusing on time series forecasting and predictive analytics.
Conduct feature engineering and optimize data models to improve accuracy and efficiency.
Continuously assess model performance using metrics like MAPE RMSE R and refine strategies as needed.
Design and implement data pipelines using PySpark SQL and cloudbased solutions for efficient data integration.
Work on largescale data integration initiatives using tools like Boomi SnapLogic SSIS or Palantir for ETL processes.
Utilize Palantir Foundry Google Cloud AutoAI and Google Colab for data modeling processing and automation.
Design and maintain data warehouse solutions to support advanced analytics and business intelligence.
Perform complex data transformations using SQL queries and data objects for AI/MLdriven projects.
Collaborate closely with business stakeholders to ensure models meet business objectives and user expectations.
Deploy monitor and continuously improve machine learning models in production environments.
Effectively communicate technical insights and findings to both technical and nontechnical stakeholders.
Proficiency in Python PySpark and SQL for data analysis feature engineering and model development.
Expertise in time series forecasting models including ARIMA Prophet LSTMs and other MLbased approaches.
Strong background in data model optimization feature engineering and performance evaluation.
Indepth understanding of ML model evaluation metrics and best practices for improving model accuracy.
Handson experience with data engineering including data pipelines ETL and data transformation processes.
Experience with tools like Boomi SnapLogic SSIS or Palantir for data integration.
Proficiency in cloud platforms particularly Google Cloud (BigQuery Vertex AI Cloud Functions etc..
Familiarity with Palantir Foundry for data processing analysis and visualization.
Ability to optimize and query largescale datasets using data lakes and relational databases.
Full Time