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Associate Experience: Hear from Veterans of the Armed Services
You will design and develop inventive products & solutions to drive innovation leveraging AI/ML/DL models
You’ll support end-to-end data science project activities including requirement analysis, explorative data analysis, data wrangling, feature engineering , algorithm selection, model fitting/validation/verification, visualization , hyper parameter tuning, inference analysis, model deployment.
You’ll use High-Performance Computing (HPC) platform to build , test , deploy AI/ML/DL models to target specific business objectives and create other business opportunities.
You’ll work with several frameworks including Spark, DASK, sci-kit learn, Xgboost, TensorFlow, Keras, PyTorch, Pandas, PyArrow.
You’ll work with several data science related tools, accelerators, and products & solutions that help with AI/ML/DL modeling.
You’ll provide post deployment support including monitoring, troubleshooting, improving model efficiency, and scaling the solution within the HPC platform.
You’ll work in a highly collaborative, team environment, and collaborating with multiple stakeholders including business, product development , architecture, and engineering teams.
You will assist management in the communication of insights and the implementation of impactful data science solutions across the organization
The ideal candidate will have a PhD or master’s degree in Economics in Statistics, Data Science, Computer Science, Applied Mathematics, or related field.
Preferred Skills, Experience:
3+ Experience with applying macroeconomic and microeconomic theories to industry cases, time series econometrics and related
• 5+ years’ experience with building, optimizing, and scaling NLP models that comb through copious amounts of data
• 5+ year experienced with drawing insights from sparsely labeled textual data and ability to leverage domain knowledge as well as ontologies to improve model performance
• 5+ years’ experience working with different algorithms using Python (including PySpark, TensorFlow, Keras, scikit-learn, Xgboost, DASK, h2o ) and/or R.
• Strong knowledge of statistical data analysis and machine learning techniques (e.g., SVM, regression, classification, clustering, time series)
• High familiarity with financial analytics, time series econometrics, payment processing and marketing strategies targeting Small and Mid-Market merchants.
• High familiarity with data platforms and applications such Snowflake, AWS Sagemaker , IBM Watson , Databricks
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