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Registration: 14.10.2024

Daria Yuferova

Specialization: Data Analyst
— Inquisitive and detail-oriented Data Analyst with experience as an HR Analyst in fintech, seeking to implement skills such as Python, SQL and data visualization tools to inform successful business decisions.
— Inquisitive and detail-oriented Data Analyst with experience as an HR Analyst in fintech, seeking to implement skills such as Python, SQL and data visualization tools to inform successful business decisions.

Portfolio

Alfa-Bank

● Calculated payroll and salary ranges for 2,000+ positions. ● Conducted job grading (Hay methodology) and benchmarking analysis. ● Conducted market research resulted in implementing new grading system. ● Participated in salary increase process and its automation. ● SAP automation (implementing enhancements, system testing). ● Annually updated salaries across the country, developed regional coefficients. 1. Job Postings for Data Analysts: ● Analysis of the US job postings dataset (20,000+ rows) and interactive geodata visualization. SQL (managing tables, aggregate functions, CTE) + Python (pandas, plotly) + Jupyter Notebook (jupysql). 2. Recipes Website Analysis: ● Web scraping recipe titles to find and visualize the most popular ingredients. Python (pandas, requests, beautifulsoup, nltk, matplotlib, wordcloud) + Jupyter Notebook.

Albioma

● Calculated and modeled the dynamics of the Gender Equality Index for 4 group companies, made suggestions for improvement. ● Conducted comparative market analysis of the compensation structure. ● Conducted market analysis to identify the best candidate profiles. ● Updated the internal job classification system (Mercer methodology). 1. Bike Rental Case Study: ● Descriptive statistics and EDA of bike rides, visualizations and recommendations. Python (pandas, matplotlib, seaborn) + Jupyter Notebook. 2. Fitness Tracker Case Study: ● Cleaning and exploring smart devices data, visualizing trends, recommendations. R (tidyverse, janitor, ggplot, patchwork) + Jupyter Notebook.

Education Index

● Conducted competitor analysis. ● Consulted the students, prepared and translated their application documents. ● Reorganized and updated the company website. ● Represented the company at 2 international educational conferences. 1. My Netflix Activity Analysis: ● Cleaning and preparing dataset to investigate and visualize viewing patterns. Python (pandas, numpy, datetime, matplotlib, seaborn) + Jupyter Notebook.

Skills

Data Analytics
Python
Data Analysis
SQL
Tableau
Microsoft Excel
Power BI
A/B testing
Git
Problem-solving
Effective communication
Google BigQuery
Data Visualization
R

Work experience

Compensation and Benefits Analyst
12.2020 - 06.2022 |Alfa-Bank
Job Grading, Microsoft Excel, Benchmarking, Automation, Market Research, SAP, SQL, Managing tables, Aggregate functions, CTE, Python, Pandas, Plotly, Jupyter Notebook, Jupysql, Requests, Beautifulsoup, Nltk, Matplotlib, Wordcloud
● Calculated payroll and salary ranges for 2,000+ positions. ● Conducted job grading (Hay methodology) and benchmarking analysis. ● Conducted market research resulted in implementing new grading system. ● Participated in salary increase process and its automation. ● SAP automation (implementing enhancements, system testing). ● Annually updated salaries across the country, developed regional coefficients. 1. Job Postings for Data Analysts: ● Analysis of the US job postings dataset (20,000+ rows) and interactive geodata visualization. SQL (managing tables, aggregate functions, CTE) + Python (pandas, plotly) + Jupyter Notebook (jupysql). 2. Recipes Website Analysis: ● Web scraping recipe titles to find and visualize the most popular ingredients. Python (pandas, requests, beautifulsoup, nltk, matplotlib, wordcloud) + Jupyter Notebook.
Compensation and Benefits Specialist
11.2019 - 08.2020 |Albioma
Project Management, Business Analysis, Job Analysis, Python, Pandas, Matplotlib, Seaborn, Jupyter Notebook, R, Tidyverse, Janitor, Ggplot, Patchwork
● Calculated and modeled the dynamics of the Gender Equality Index for 4 group companies, made suggestions for improvement. ● Conducted comparative market analysis of the compensation structure. ● Conducted market analysis to identify the best candidate profiles. ● Updated the internal job classification system (Mercer methodology). 1. Bike Rental Case Study: ● Descriptive statistics and EDA of bike rides, visualizations and recommendations. Python (pandas, matplotlib, seaborn) + Jupyter Notebook. 2. Fitness Tracker Case Study: ● Cleaning and exploring smart devices data, visualizing trends, recommendations. R (tidyverse, janitor, ggplot, patchwork) + Jupyter Notebook.
Education Abroad Consultant
11.2017 - 06.2019 |Education Index
B2C, CRM, Python, Pandas, Numpy, Datetime, Matplotlib, Seaborn, Jupyter Notebook
● Conducted competitor analysis. ● Consulted the students, prepared and translated their application documents. ● Reorganized and updated the company website. ● Represented the company at 2 international educational conferences. 1. My Netflix Activity Analysis: ● Cleaning and preparing dataset to investigate and visualize viewing patterns. Python (pandas, numpy, datetime, matplotlib, seaborn) + Jupyter Notebook.

Educational background

International HR Management (Masters Degree)
2019 - 2020
Université Paris II
Public Administration (Bachelor’s Degree)
2015 - 2019
Higher School of Economics

Languages

ruNativegbProficientfrAdvanceddeAdvanced