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Data Analytics : Data Scientist at Remote, Remote, USA

Email: [email protected]

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Eli,

R Cube

[email protected]

Reply to:   [email protected]

Data Analytics : Data Scientist

        Bachelor's degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline is required; OR 4 years of related statistics, mathematics or quantitative analytics or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.

        6 years of data & analytics experience; OR 4 years of data & analytics experience and up to 2 years of progressive functional business relevant experience within the respective industry of responsibility (i.e. P&C, Bank, Finance, Marketing etc.) for a total of 8 years combined experience; OR Advanced degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline and 6 years of experience in data/analytics or functional business experience within the respective industry of responsibility (i.e. P&C, Bank, Finance, Marketing, etc.).

        Demonstrates expert skills in mathematical and statistical techniques and approaches used to drive fact-based decision-making.

        Expert knowledge of Python (for Data Science), SQL, R Programming, ML & Predictive Analytics Algorithm.

        Gitlab CI/CD Pipeline & Devops/MLOps for building ML Pipeline, Deployment experience/knowledge of ML/Financial Models in Cloud, Familiar with Docker images.

        Good understanding of financial modeling/ML models, Experience & knowledge of Data Warehouse, Hadoop & Distributed computing.

        Preferred : AWS ML Certified, AWS Sagemaker, Snowflake, Airflow, Domino Data Lab, RedHat Openshift.

Keywords: cprogramm continuous integration continuous deployment machine learning rlang

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Wed Aug 16 18:45:00 UTC 2023

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eli@rcubecreativeconsulting.com wrote:
From:

Eli,

R Cube

eli@rcubecreativeconsulting.com

Reply to:   eli@rcubecreativeconsulting.com

Data Analytics : Data Scientist

Bachelor's degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline is required; OR 4 years of related statistics, mathematics or quantitative analytics or related experience (in addition to the minimum years of experience required) may be substituted in lieu of degree.

6 years of data & analytics experience; OR 4 years of data & analytics experience and up to 2 years of progressive functional business relevant experience within the respective industry of responsibility (i.e. P&C, Bank, Finance, Marketing etc.) for a total of 8 years combined experience; OR Advanced degree in quantitative analytics field such as Economics, Finance, Statistics, Mathematics, Actuarial Sciences, Operations Research, Data and/or Business Analysis, Data Science or other quantitative discipline and 6 years of experience in data/analytics or functional business experience within the respective industry of responsibility (i.e. P&C, Bank, Finance, Marketing, etc.).

Demonstrates expert skills in mathematical and statistical techniques and approaches used to drive fact-based decision-making.

Expert knowledge of Python (for Data Science), SQL, R Programming, ML & Predictive Analytics Algorithm.

Gitlab CI/CD Pipeline & Devops/MLOps for building ML Pipeline, Deployment experience/knowledge of ML/Financial Models in Cloud, Familiar with Docker images.

Good understanding of financial modeling/ML models, Experience & knowledge of Data Warehouse, Hadoop & Distributed computing.

Preferred : AWS ML Certified, AWS Sagemaker, Snowflake, Airflow, Domino Data Lab, RedHat Openshift.

Keywords: cprogramm continuous integration continuous deployment machine learning rlang

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