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Metro location and general Data Scientist title increase applicant competition moderately.
Core data science skills are highly transferable across industries despite optional energy domain experience.
Several mandatory technical skills (R, caret, xgboost, Databricks) but no explicit years requirement.
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Own development and deployment of data science solutions using R programming, including data manipulation, statistical analysis, and machine learning.
Build and maintain data visualizations and dashboards (ggplot2, Shiny) to aid client decision-making.
Collaborate on agile projects supporting large clients in financial services, leveraging Databricks and Git-based version control.
Strong proficiency in R programming (RStudio, tidyverse packages like dplyr, tidyr).
Experience with machine learning techniques such as caret, randomForest, and xgboost.
Familiarity with data visualization tools: ggplot2, Shiny dashboards.
Work Experience Required: Not explicitly mentioned in the JD.
Experienced in data science projects within financial services or a related domain, with preference for energy sector exposure.
Comfortable working in Agile/Scrum environments with version control (Git) and data engineering platforms (Databricks).
Skilled in statistical and probabilistic modeling to support transformation projects and analytics delivery at scale.