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FedEx needs someone good with details to look at their data and numbers. You’ll be the new Data Analyst. Your job is digging into those complex data sets and turning them into something the big bosses can use to make good choices for the company. The stuff you pull out will help FedEx keep improving how they get packages delivered.
Job Description :-
| Company Name | Fedex |
| Job Role | Data analyst |
| Qualification | Any Degree |
| Experience | Fresher/Experienced |
| Batch | Any Batch |
| Location | Bangalore, India |
| CTC/Salary | Not Disclosed |
Tips to Prepare an ATS-Friendly Resume :-
Getting your resume noticed by the Applicant Tracking System is super important if you want employers to actually see it. I’ll give some tips to help make your resume look good to the computer system if you’re applying to be a Data Scientist.
1. Keep it simple. Don’t use crazy fonts, tables, or anything too wild. Stick to basics like clear section headings (“Skills,” “Experience”).
2. Load up on keywords. Pull words right from the job description – Python, Machine Learning, whatever. Show you have the technical and people skills they want.
3. Use normal job titles. “Data Scientist” or “Analyst,” not “Future CEO.”
4. Put key info in the body text. No footers! Recruiters might not see em. Keep your name, address, LinkedIn front and center.
5. Save as a .docx or .pdf file. Make sure the pdf isn’t an image or anything weird. Give it a professional name too like “FirstName_LastName_Resume”.
6. Show you got the right background. Internships, projects, anything to prove you can handle a Data Science job. Numbers help – “improved model by 15%” tells em you get results.
7. Use bullet points, not paragraphs. Easier to scan.
8. Show off certifications and schoolin’. DataCamp, Coursera courses, a math/CS degree – make em shine! 9. Nix the images and logos. Recruiters tech can’t handle em.
10. List technical skills first. Python, R, SQL – they wanna see you have these specifically.
11. Check for typos! Sloppy resumes might get tossed by the robot gatekeepers.
12. Test it out first. Free online tools can scan your resume before you submit to catch issues.
Follow this advice and you’ll be all set to pass the ATS recruiters and get that interview!
Tips for acing the job interview:-
Do’s:
– Look into the company and the stuff they need help with.
– If you don’t get something, ask them to explain More.
– Walk them through how you think about fixing problems.
– Use real examples from past work to show your skills.
– Stay calm and confident. Work through problems slowly, even if you aren’t sure.
Don’ts:
– Don’t guess if you aren’t sure. Explain your thinking.
– Keep your answers simple and clear.
– Remember to talk about teamwork, communication, and problem fixing.
– Take your time to think before answering.
– Ask good questions to show you care about the job and team.
Eligibility / Qualification:-
- Know-how in analytics or consulting or working with data.
- Key abilities: –
- Crunching data and figuring out business stuff
- Using advanced math and models to predict things
- Working with higher ups and team players
- Managing projects
- Background in pricing and making money from customers. Understanding stuff like: –
- Finding the best price where you make the most money
- Separating customers into groups based on what they will buy
- Calculating how pricing decisions impact revenue
- Some exposure to predicting trends with AI/ML is a bonus
- Education – MBA or Masters focusing on computer stuff, math, engineering/business statistics – preferably from a top university
- Experience with tools like Oracle, SQL Server, Python, Tableau
- Good bonus skills – understanding cloud computing, big data, Azure
What You Do:-
- Find data inside and outside the company to analyze
- Team up with experts to pick the best data sources
- Dig into different data sets to learn new stuff
- Keep up with new technology to analyze data faster
- Use their math smarts to solve tricky data problems
- Come up with ways to find patterns and connections in the data
- Put together important info to figure out “if this, then that”
- Work with teams in loops
- share findings, get feedback, share more
- Check that their analyses makes sense for the business goals
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