IndiaLends

Developed and optimized 13 product funnels in SQL for personal loans, identifying key drop-offs and achieving a 15% increase in offer selection rate.

Worked directly with Product Managers, partnering with developers and tech teams to troubleshoot and resolve API issues, reducing rejections by 17%. Supported backend improvements for CRM automation, boosting accuracy by 20%.

Conducted extensive testing on 30+ APIs with Postman, resolving inconsistencies for 5 major lender integrations and documenting processes to streamline troubleshooting by 40%.

Built 8 Clevertap funnels to analyze offer page interactions, improving offer selection by 8%.

Maintained MIS reports with 99% accuracy, coordinating with Growth and Tech teams to resolve data inconsistencies.

Analyzed 60000+ loan disbursals, identifying top rejection reasons and advising on updates that boosted disbursals by 12%.

Consolidated 15+ lender API data sources, reducing data retrieval time by 30% for efficient reporting.

Product Analyst Intern

Leadle

• Wrote SQL queries to extract data from databases efficiently. Developed, maintained, and optimized SQL Queries and stored procedures.
• Collaborated with RevOps team and maintained live prospects dashboard on Google Looker Studio, connected with Google Sheets
• Prepared and cleaned data for analysis, including data normalization, aggregation, and transformation. (SQL, Excel and Tableau)
• Ensured accurate data by performing thorough validation and quality checks. Worked together with business and data teams to comprehensively grasp the data requirements and objectives.
• Leveraged the power of data visualization using sophisticated tools like Tableau to create captivating and informative reports and dashboards. Presented the findings to stakeholders in a visually engaging and interactive manner, unleashing the full potential of data-driven insights. Translated complex data into clear and understandable visual representations.

Data Analyst

5X your AI & Data Science skills. Get free AI guides and resources ⬇️

I like writing about Data. 

Working as a Product Analyst in a Fintech startup.

I've started writing on LinkedIn from 2023 as part of my job search. 

(Then it became addictive!)

This platform became a powerful aid in my growth journey.

I'm fortunate to meet some amazing people via LinkedIn.

I write about my learnings and opinions on Data career.

Enquiries/Collab: contact.leonjose@gmail.com

Apple SQL interview questions for data analyst:

I've put together top 4 interview questions from Apple for your practice.

These are similar to recently asked SQL questions at Apple.

1. 𝑇𝑟𝑎𝑑𝑒-𝐼𝑛 𝑅𝑒𝑣𝑒𝑛𝑢𝑒 𝑏𝑦 𝑆𝑡𝑜𝑟𝑒
 
𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭: Write a query to calculate the total revenue from trade-in payouts for each store. Ensure the results are ordered by total payout in descending order. 

2. 𝐴𝑖𝑟𝑃𝑜𝑑𝑠 𝑃𝑢𝑟𝑐ℎ𝑎𝑠𝑒 𝑃𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 

𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭: Determine the percentage of customers who bought AirPods immediately after purchasing iPhones. Round the result to the nearest whole number. 

3. 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑀𝑜𝑛𝑡ℎ𝑙𝑦 𝑆𝑎𝑙𝑒𝑠 𝑜𝑓 𝐴𝑝𝑝𝑙𝑒 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 

𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭: Compute the average quantity of each Apple product sold per month for the year 2021. This analysis should help assess product performance over time. 

4. 𝐴𝑣𝑒𝑟𝑎𝑔𝑒 𝑅𝑎𝑡𝑖𝑛𝑔𝑠 𝑜𝑓 𝐴𝑝𝑝𝑙𝑒 𝑃𝑟𝑜𝑑𝑢𝑐𝑡𝑠 

𝐏𝐫𝐨𝐛𝐥𝐞𝐦 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭: Calculate the monthly average rating for each Apple product based on user reviews. The analysis should span the entire year, providing insights into product performance.

------------------------------------------

Want to upskill in Data Analytics?

Learn Power BI, SQL & Power Query in live weekend classes.

🎓 10% off with code: DATALEON10 

https://lnkd.in/gJjvuQv9



#sql #dataanalyst

Leon Jose

Product @SaveIN | AI | FinTech | Analytics

Apple SQL Interview Questions for Data Analyst

Excel topics for Data Analyst interview. Bookmark this post 👇

- Basic functions: SUM, AVERAGE, MIN, MAX, COUNT, and COUNTIF etc.

- VLOOKUP, HLOOKUP and XLOOKUP: Using these functions to look up data in tables.

- Pivot tables: Creating and manipulating pivot tables, formatting pivot tables, and using slicers.

- Data cleaning and transformation: Removing duplicates, data sorting and filtering, and using text functions (LEFT, RIGHT, MID, CONCATENATE, etc.).

- Conditional formatting: Applying colors, data bars, and icons based on specific conditions.

- Charts and graphs: Creating and customizing charts and graphs (bar, line, pie, scatter, etc.).

- Macros: Recording and running macros to automate repetitive tasks.

- Data validation: Creating drop-down lists and using custom validation rules.

- Statistical analysis: Basic statistical functions (STDEV, CORREL, etc.) and using data analysis add-ins (Regression, ANOVA, etc.).

- Formula auditing: Tracing formula precedents and dependents, and using the Evaluate Formula tool.

credits: Financial Modeling World Cup

-------------------------------------------------------
♻️ Found this useful, Repost!

(Join my WhatsApp community: Link in comments 👇)


#dataanalyst #excel

Taplio

Leon Jose's Linkedin Analytics

's Best Posts (last 30 days)

Want to drive more opportunities from LinkedIn?

Taplio

.css-1jgreyo{background-image:linear-gradient(284deg, rgba(39,43,72,1) 0%, rgba(33,47,183,1) 100%);color:transparent;-webkit-background-clip:text;background-clip:text;}Leon Jose's Linkedin Analytics

's Best Posts .css-qqfgvy{font-size:var(--chakra-fontSizes-md);}(last 30 days)

Want to drive more opportunities from LinkedIn?

Leon Jose's Linkedin Analytics

's Best Posts (last 30 days)