Phong cách CV tuyệt vời

% Emulates the well known Awesome-CV look (colored name accent, bold section
% rules, right aligned dates) using only standard packages. The Awesome-CV
% class itself is not vendored.
\documentclass[10pt,a4paper]{article}
\usepackage[margin=0.75in]{geometry}
\usepackage{xcolor}
\usepackage{enumitem}
\usepackage[hidelinks]{hyperref}
\definecolor{accent}{HTML}{117A65}
\setlist[itemize]{leftmargin=1.1em, itemsep=1pt, topsep=2pt, parsep=0pt}
\newcommand{\sect}[1]{\vspace{9pt}{\color{accent}\Large\bfseries #1}\\[-5pt]{\color{accent}\rule{\linewidth}{1.6pt}}\\[3pt]}
\newcommand{\role}[3]{\textbf{#1} \hfill {\small\color{accent} #3}\\ {\small\itshape #2}}
\pagestyle{empty}

\begin{document}

\begin{center}
{\fontsize{30}{34}\selectfont\bfseries\color{accent} Marta Kowalski}\\[3pt]
{\Large Data Scientist}\\[6pt]
{\small [email protected] \quad Krakow, Poland \quad linkedin.com/in/mkowalski \quad github.com/mkowalski}
\end{center}
\vspace{2pt}
{\color{accent}\rule{\linewidth}{1.6pt}}

\sect{Experience}
\role{Senior Data Scientist}{Baltic Analytics}{2021 -- present}
\begin{itemize}
  \item Built the demand forecasting model that cut warehouse overstock by 18 percent across 40 stores.
  \item Lead a team of four and set the review standards for all production machine learning code.
\end{itemize}

\role{Data Scientist}{Vistula Retail Group}{2018 -- 2021}
\begin{itemize}
  \item Shipped a churn prediction pipeline serving 2 million customer scores weekly.
  \item Automated the monthly reporting suite, saving the analytics team two days per cycle.
\end{itemize}

\sect{Education}
\role{M.Sc. Statistics}{Jagiellonian University}{2016 -- 2018}
\role{B.Sc. Mathematics}{AGH University of Krakow}{2012 -- 2016}

\sect{Skills}
\textbf{Languages:} Python, R, SQL, Scala\\[2pt]
\textbf{Tools:} scikit-learn, PyTorch, Airflow, Spark, dbt\\[2pt]
\textbf{Focus areas:} forecasting, causal inference, experimentation

\sect{Publications}
\begin{itemize}
  \item Kowalski, M. et al. Robust demand forecasting under promotional shocks. Journal of Retail Analytics, 2023.
\end{itemize}

\end{document}