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:
- Time allocation principle: Focus on securing interview opportunities before receiving any interviews; once an interview is secured, focus on interview preparation.
- Take action first, then reflect and improve as you go.
Therefore, we start with the resume, which includes two important factors:
- A well-formatted resume.
- 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 :
- Choose project topics that are valuable and eye-catching.
- Analyze the data methodically and highlight key insights.
- 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:
- Based on this information and my experience, write a resume for a Data Engineer.
- Create a consulting website to showcase a data consultant’s service offerings.