Experience: 0-2 years
Agar tum Data Analytics me career banana chahte ho aur ek world-class company me kaam karne ka sapna hai, toh yeh post dhyan se padho. American Express ne Gurugram me Analyst – Data Analytics ke liye opening nikali hai. Role hybrid hai, package competitive hai, aur company ki reputation toh sabko pata hi hai. Yeh opportunity sirf 0 se 2 saal ke experienced candidates ke liye bhi hai — yani freshers bhi apply kar sakte hain agar skills strong hain.
Apply karne ki last date 26 June 2026 hai — toh jaldi karo.
American Express Ke Baare Me
American Express yaani Amex ek 175 saal purani American financial services company hai. Credit cards, payment solutions aur travel services — yeh sab inke core business hain. Duniya ke sabse trusted financial brands me se ek hai yeh.
India me Gurugram me inki ek badi office hai jahan analytics, technology aur marketing teams kaam karti hain. Amex me kaam karna matlab world-class culture, strong learning opportunities aur ek aise environment me hona jahan tumhari awaaz matter karti hai.
Job Ki Poori Detail
| Detail | Jankari |
|---|---|
| Position | Analyst – Data Analytics (Band 30) |
| Company | American Express |
| Location | Gurugram, Haryana (Hybrid) |
| Job Type | Full Time |
| Shift | Rotating / Flexible |
| Posted On | 18 June 2026 |
| Last Date to Apply | 26 June 2026 |
| Experience | 0 – 2 Saal |
| Team | AIM – Analytics, Investment & Marketing Enablement |
Yeh Role Kis Team Me Hai?
Yeh role AIM Team yaani Analytics, Investment and Marketing Enablement team ka hissa hai jo Amex ke Global Commercial Services यानी GCS Marketing division ke under aati hai. Simple words me — yeh team Amex ke business ko data-driven decisions lene me help karti hai.
Is role me tumhara kaam hoga Acquisition Campaign Measurement Analytics — matlab yeh samajhna ki Amex ke marketing campaigns kitne effective hain, kaunse channels kaam kar rahe hain, aur business growth ke liye kya insights diye ja sakte hain.
Kaam Kya Karna Hoga?
- Business partners ke saath milke campaign measurements aur ROI analysis karna hoga
- Data analysis karke actionable insights nikalni hongi jo GCS business strategy ko guide karen
- Monthly results reporting accurately aur time pe deliver karni hogi marketing aur sales leadership ke liye
- Multiple data sources se data explore karna hoga aur unhe clear visual case studies me present karna hoga
- Stakeholders se requirements gather karna, analysis karna aur results clearly present karna hoga
- Business needs assess karne ke liye functional aur senior leaders ke saath collaborate karna hoga
- Marketing stakeholders ke saath strong relationship build karni hogi aur projects end to end drive karne honge
Eligibility – Kaun Apply Kar Sakta Hai?
Education:
Quantitative field me degree preferred hai — B.Tech, BSc/MSc Statistics, ya Economics me Bachelors ya Masters.
Zaroori Skills:
- SQL — data manipulation ke liye strong command honi chahiye
- Python — data analysis aur automation ke liye
- Hive aur PySpark — large scale data processing ke liye
- Tableau ya Power BI — data visualization ke liye
- Advanced Excel — basic but must-have
Preferred Skills:
- GenAI ka knowledge ya exposure
- Statistical techniques ka knowledge — hypothesis testing, regression, KNN, t-test, chi-square test
- Campaign measurement ya marketing analytics ka experience
- R language bhi acha to have hai
Soft Skills Jo Chahiye:
- Strong communication — results aur methods clearly explain kar sako
- High pressure me kam errors ke saath kaam karne ki ability
- Self-driven hona — minimum supervision me kaam kar sako
- Growth mindset aur status quo ko challenge karne ki aadat
- Team me effectively kaam karna aana chahiye
Ek Zaroori Baat: Flexible shift timings ke liye comfortable rehna hoga kyunki Global Partners ko support karna hota hai alag time zones me.
Yeh Job Kyun Karni Chahiye?
Brand: American Express ka naam resume pe hona apne aap me ek achievement hai. Finance aur tech dono worlds me yeh naam bahut respect rakhta hai.
Hybrid Work: Office aur ghar dono se kaam karne ki flexibility hai — 100% office nahi hai.
Learning aur Growth: Amex me training, career development programs aur leadership opportunities openly milte hain. Ek baar andar aao toh growth ki kami nahi hogi.
World-Class Benefits: Competitive salary ke saath bonus incentives, health insurance, dental, vision, life insurance, mental health support, parental leave — sab kuch cover hota hai.
Real Impact: Yahan jo kaam hoga woh directly Amex ke global business decisions ko influence karega — koi busywork nahi.
👉 Direct Apply Link
Click Here to Apply – American Express Analyst Data Analytics Job
⚠️ Last Date: 26 June 2026 — bahut kam time bacha hai, abhi apply karo.
Interview Ki Taiyari – Yeh Questions Zaroor Padho
American Express ka interview multi-round hota hai — technical round, case study round aur HR round. Niche sabse important questions diye hain.
SQL Questions
Q. What is the difference between WHERE and HAVING clause?
WHERE clause filters rows before grouping happens. HAVING clause filters groups after the GROUP BY operation is applied. For example, if you want to find departments with more than 10 employees, you would use HAVING COUNT(*) > 10, not WHERE.
Q. What are window functions in SQL? Give an example.
Window functions perform calculations across a set of rows related to the current row without collapsing them into a single output like GROUP BY does. Common examples are ROW_NUMBER(), RANK(), DENSE_RANK(), LAG(), and LEAD(). For example, ROW_NUMBER() OVER (PARTITION BY department ORDER BY salary DESC) gives each employee a rank within their department based on salary.
Q. What is the difference between INNER JOIN, LEFT JOIN, and FULL OUTER JOIN?
INNER JOIN returns only the rows that have matching values in both tables. LEFT JOIN returns all rows from the left table and matching rows from the right — non-matching right rows show NULL. FULL OUTER JOIN returns all rows from both tables, with NULLs where there is no match on either side.
Q. How would you find duplicate records in a table?
Use GROUP BY on the columns you want to check for duplicates, then use HAVING COUNT() > 1. For example: SELECT email, COUNT() FROM users GROUP BY email HAVING COUNT(*) > 1.
Q. What is indexing and why is it important?
An index is a database structure that speeds up data retrieval. Without an index, the database scans every row to find matching records. With an index on a frequently queried column, it jumps directly to the relevant rows — making queries significantly faster on large datasets.
Python Questions
Q. What is the difference between a list and a tuple in Python?
A list is mutable — you can add, remove, or change elements after creation. A tuple is immutable — once created, it cannot be changed. Tuples are faster and use less memory, making them suitable for fixed data like coordinates or configuration values.
Q. How do you handle missing values in a Pandas DataFrame?
You can check for missing values using df.isnull().sum(). To handle them, you can either drop rows or columns using df.dropna(), fill them with a specific value using df.fillna(value), or fill with the mean or median of the column using df.fillna(df[‘column’].mean()).
Q. What is the difference between apply() and map() in Pandas?
map() works on a single Series and is used for element-wise operations. apply() works on both Series and DataFrames and can apply a function along an axis — row-wise or column-wise. For complex transformations on a DataFrame, apply() is more flexible.
Q. How would you merge two DataFrames in Pandas?
Use pd.merge(df1, df2, on=’common_column’, how=’inner’) — the how parameter works like SQL JOINs. You can use ‘inner’, ‘left’, ‘right’, or ‘outer’ depending on what data you want to retain.
Q. What is the use of groupby() in Pandas?
groupby() splits the data into groups based on one or more columns, then lets you apply aggregate functions like sum(), mean(), count(), or max() on each group. It is the Pandas equivalent of SQL’s GROUP BY clause.
Statistics & Analytics Questions
Q. What is hypothesis testing?
Hypothesis testing is a statistical method to determine whether there is enough evidence in a sample to support a claim about a population. You define a null hypothesis (H0) and an alternative hypothesis (H1), then calculate a p-value. If the p-value is below the significance level (usually 0.05), you reject the null hypothesis.
Q. What is the difference between a t-test and a chi-square test?
A t-test is used to compare the means of two groups — for example, did Campaign A generate higher average spend than Campaign B. A chi-square test is used for categorical data — for example, is there a significant relationship between customer segment and product preference.
Q. What is regression analysis?
Regression analysis is used to understand the relationship between a dependent variable and one or more independent variables. Linear regression predicts a continuous output, while logistic regression predicts a binary outcome like yes or no. In marketing analytics, regression helps quantify the impact of different campaign variables on conversion rates.
Q. What is the difference between correlation and causation?
Correlation means two variables move together — when one increases, the other tends to increase or decrease. Causation means one variable directly causes the change in the other. A classic mistake in analytics is assuming correlation implies causation — which is not always true. Always validate with controlled experiments or deeper analysis.
Q. What is campaign ROI and how do you calculate it?
Campaign ROI measures how much revenue a marketing campaign generates relative to its cost. The formula is: ROI = (Revenue Generated – Campaign Cost) / Campaign Cost × 100. In practice, attributing revenue precisely to a single campaign requires careful measurement across channels.
Tableau / Power BI Questions
Q. What is the difference between Tableau and Power BI?
Both are data visualization tools, but they have different strengths. Tableau is more powerful for complex visual analytics and handles large datasets very smoothly. Power BI integrates tightly with Microsoft products like Excel and Azure and is more cost-effective for organizations already using the Microsoft ecosystem.
Q. What is a calculated field in Tableau?
A calculated field lets you create new data from existing fields using formulas — similar to writing a formula in Excel. For example, you can create a profit margin field by dividing profit by sales directly within Tableau without modifying the original data source.
HR & Behavioral Questions
Q. Tell me about yourself.
Start with your educational background, mention the tools and skills you have worked with — especially SQL, Python, and any analytics projects — and then explain why you are excited about this specific role at American Express. Keep it to 2-3 minutes and stay relevant.
Q. Why do you want to work at American Express?
Talk about Amex’s reputation as a data-driven company, their focus on innovation in financial services, and how the AIM team’s work in campaign analytics aligns with your interest in marketing data. Show that you have done your research.
Q. Tell me about a project where you used data to solve a business problem.
Pick a real project — from college, internship, or personal work. Describe the problem clearly, what data you used, what analysis you performed, and what insight or outcome came out of it. Numbers make the story stronger — mention them if you have them.
Q. How do you handle ambiguity in a project?
Say that you start by breaking the problem down into smaller, more defined questions. You gather as much context as possible from stakeholders, make reasonable assumptions clearly, and validate your approach before going deep. Mention that you stay comfortable with iteration.
Q. How do you explain complex data findings to a non-technical audience?
Say that you focus on the business impact, not the technical process. You use simple charts and clear language, avoid jargon, and always start with the “so what” — what does this data mean for the business decision at hand.
Apply Karne Se Pehle Yeh Checklist Dekho
✅ Resume me SQL, Python, aur koi bhi data analytics project clearly mention karo
✅ Agar koi Tableau ya Power BI dashboard banaya ho toh uska screenshot ya link ready rakho
✅ Statistical techniques — regression, hypothesis testing — inhe resume me mention karo agar knowledge hai
✅ GitHub pe koi data project upload kiya hua hai toh link ready rakho
✅ Last date 26 June hai — ek bhi din mat barbad karo
Aakhri Baat
American Express jaisi company me Analyst ki role milna ek badi achievement hoti hai. Yeh sirf ek job nahi hai — yeh ek aisa platform hai jahan tum genuinely world-class analytics kaam seekh sakte ho aur apna career strong foundation pe khada kar sakte ho.
Agar SQL aur Python me confidence hai aur data se insights nikalna tumhara passion hai, toh yeh role tumhare liye hi bani hai.
👉 Abhi Apply Karo – American Express Data Analytics Analyst, Gurugram
Yeh post apne un doston ke saath share karo jo data analytics, SQL ya Python me hain — unhe bhi yeh mauka zaroor milna chahiye. Aur aisi aur private job vacancies ke liye humara blog bookmark karke rakho.