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Preparing for data jobs means writing a good resume and passing the job interview.

I want to take immediate action, so I’ve set the following principles:

  1. Time allocation principle: Focus on securing interview opportunities before receiving any interviews; once an interview is secured, focus on interview preparation.
  2. Take action first, then reflect and improve as you go.

Therefore, we start with the resume, which includes two important factors:

  1. A well-formatted resume.
  2. Projects that make me stand out.

1 Resume

The way to achieve a well-formatted resume is through imitation.

1.1 Skills example

  • Programming Languges : Python(Pandas, NumPy, SciPy, MatPlotLib, Pytorch)
  • Database : MS SQL Server, MySQL
  • BI&Visualization Tools : PowerBI, Tableau, MS Excel(Pivot Table, VLOOKUP, Conditional Formatting)

1.2 Projects example

example 1 : Customer Market Analysis :

  • Created a dynamic dashboard using PowerBI, resulting in 8 visualizations of market trends and the identification of previously unnotived customer markets.
  • Analyzed 8, 000 transactional rows using Python to identify 3 distinct customer categories and the formulation of 2 different market strategies.
  • Create 5 KPIs to identify market opportunities and actionable insights including which customer markets to target based on customer activity.

example 2 : Automated Employee Reporting System :

  • Analyzed employee performance metrics using SQL queries to increase employee productivity and identify high-performing departments.
  • Automated a reoprting system using SQL and Excel VBA to streamline data extraction and analytics, improving the reporting time by 20%
  • Cleansed and preprocessed 10, 000 rows using Pandas in Python to prepare data for analysis and gain insights on employee performance, resulting in a 25% reduction in data processing time.

example 3 : Sales Performance Analytics :

  • Analyzed sales performance of 20, 000 employees using Excel to identify trends and patterns, enabling a 20% faster understanding of sales performance.
  • Summarized total sales with 3 charts by using the dimensions region, product category, and time, allowing the user to dynamically identify key metrics impacting sales.
  • Interpreted trends in 2 complex data sets by finding correlations between them and visualizing the results using SQL and PowerBI.

1.3 Work experience example

example 1 : Cleaning Assistant :

  • Implemented cleaning procedures and schedules, increasing productivity by 10%
  • Maintained monthly cleaning records and sales reports in Excel to track of financial analysis, resulting in a 20% reduction in time spent on data retrieval.
  • Initiated a new sales strategy to improve customer retention rates that boosted monthly sales by 5%

example 2 : teacher :

  • Using Excel functions to assess and evaluate student progress, reducing the turnaround time from 3 days to 1 day.
  • Created metrics for a monthly automated report to communicate student performance to parents, leading to a 15% increase in parental engagement.
  • Analyzed trends of 30 student grades by subject and automated weekly student reports resulting in a saving of 5 hours a week

2 Build projects to apply for job

I use the following criteria to evaluate and select suitable projects.

2.1 Evaluation system

Advice from a recruiter :

  1. Choose project topics that are valuable and eye-catching.
  2. Analyze the data methodically and highlight key insights.
  3. Present your project outcomes in a way that’s tailored for job applications.

2.2 Common types

Common types of data-related presentation projects :

Type Presentation format
Insight Report report
Dashboard public Dashboard
Predictive Model github+report/Jupyter

3 Practical plan

I plan to accomplish two things:

  1. Based on this information and my experience, write a resume for a Data Engineer.
  2. Create a consulting website to showcase a data consultant’s service offerings.