Junior Data Scientist Engineer @ Patterned Learning Career | Jobright.ai
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Patterned Learning Career ยท 2 days ago

Junior Data Scientist Engineer

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IT System Operations and Maintenance

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Responsibilities

Utilize R or Python for data analysis and modeling.
Demonstrate proficiency in statistical programs like R, SAS, MATLAB, or Python.
Work with spreadsheets (VBA) and database applications (Access, Oracle, SQL, or equivalent technology).
Apply basic understanding of SQL, Javascript, XML, JSON, and HTML.
Learn new methods quickly and work under deadlines.
Collaborate effectively in a team setting and communicate well.
Leverage strong analytical and problem-solving abilities.
Utilize actuarial concepts and statistical modeling techniques such as GLM, Decision Trees, Time Series, Regression, etc.
Employ Microsoft DeployR, insurance risk analysis, computational finance, econometrics, statistics, and math.
Apply SQL, VBA, R, Python for predictive modeling.

Qualification

Find out how your skills align with this job's requirements. If anything seems off, you can easily click on the tags to select or unselect skills to reflect your actual expertise.

RPythonStatistical programsSpreadsheets (VBA)Database applicationsSQLJavascriptXMLJSONHTMLDeadline managementProblem-solvingTeamworkCommunicationActuarial ConceptsStatistical ModelingMicrosoft DeployRInsurance Risk AnalysisComputational FinanceEconometricsStatisticsVBAPredictive Modeling

Required

Strong knowledge of R or Python for data analysis and modeling.
Proficiency in statistical programs such as R, SAS, MATLAB, or Python.
Familiarity with spreadsheets (VBA) and database applications (Access, Oracle, SQL, or equivalent technology).
Basic understanding of SQL, Javascript, XML, JSON, and HTML.
Ability to learn new methods quickly and work under deadlines.
Excellent teamwork and communication skills.
Strong analytical and problem-solving abilities.
Basic understanding of SQL, Javascript, XML, JSON, and HTML.

Preferred

Knowledge of actuarial concepts and life, health, and/or annuity products.
Experience with statistical modeling techniques such as GLM, Decision Trees, Time Series, Regression, etc.
Familiarity with Microsoft DeployR.
Exposure to insurance risk analysis.
Basic experience in computational finance, econometrics, statistics, and math.
Knowledge of SQL and VBA.
Familiarity with R or Python for predictive modeling.

Company

Patterned Learning Career

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Funding

Current Stage
Early Stage
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