Eli Lilly Senior Data Analyst Interview Experience – ₹22 LPA SQL, Python, Tableau, Case Studies

Eli Lilly Senior Data Analyst Interview Experience (CTC – ₹22 LPA)

One of my friends recently appeared for Eli Lilly’s Senior Data Analyst role — and the interview process was a perfect blend of data engineering, analytics, and domain-focused problem-solving.
Here’s how the rounds unfolded

⸻

Round 1: SQL (Technical Assessment)

Eli Lilly focuses heavily on complex joins, subqueries, and analytics on healthcare datasets.

Some questions included:

1. Find patients who were prescribed Drug A and Drug B within the same 30-day period.

2. Calculate month-over-month change in drug sales per region using window functions.

3. Identify duplicate patient records and methods to clean them efficiently.

4. Write a query to find the average time gap between diagnosis and first treatment per patient.

Round 2: Python + Data Cleaning Case

1. Given a messy CSV with nulls, outliers, and inconsistent date formats — clean and standardize it using pandas.

2. Derive meaningful KPIs such as Average Prescription per Doctor and Total Active Patients.

3. How would you automate data validation in a production pipeline?

Round 3: Tableau + Storytelling

1. Create a visualization for prescription patterns across age groups and regions.

2. Build a dashboard showing treatment adherence rates and highlight insights for leadership.

3. How do you ensure clinical data confidentiality while visualizing trends?

⸻

Round 4: Business Case + Domain Understanding

1. The sales team reports a drop in insulin drug revenue. How will you identify the cause?

2. What KPIs would you define for patient retention programs?

3. How would you measure the success of a new drug launch campaign?

⸻

Round 5: Managerial Round

1. How do you balance data accuracy and reporting speed under tight deadlines?

2. Describe a time when your data recommendation was rejected — what did you learn?

3. How do you collaborate with medical and non-technical stakeholders?

⸻

✨ Pro Tip:

Eli Lilly focuses on data integrity, reproducibility, and domain-driven insights.

If you can combine technical expertise with healthcare understanding, you’ll stand out.

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Eli Lilly Senior Data Analyst Interview EXP

Eli Lilly Senior Data Analyst Interview Experience (CTC – ₹22 LPA)

One of my friends recently appeared for Eli Lilly’s Senior Data Analyst role — and the interview process was a perfect blend of data engineering, analytics, and domain-focused problem-solving.
Here’s how the rounds unfolded

Round 1: SQL (Technical Assessment)

Eli Lilly focuses heavily on complex joins, subqueries, and analytics on healthcare datasets.

Some questions included:

Round 2: Python + Data Cleaning Case

1. Given a messy CSV with nulls, outliers, and inconsistent date formats — clean and standardize it using pandas.

2. Derive meaningful KPIs such as Average Prescription per Doctor and Total Active Patients.

3. How would you automate data validation in a production pipeline?

Round 3: Tableau + Storytelling

1. Create a visualization for prescription patterns across age groups and regions.

2. Build a dashboard showing treatment adherence rates and highlight insights for leadership.

3. How do you ensure clinical data confidentiality while visualizing trends?

Round 4: Business Case + Domain Understanding

1. The sales team reports a drop in insulin drug revenue. How will you identify the cause?

2. What KPIs would you define for patient retention programs?

3. How would you measure the success of a new drug launch campaign?

Round 5: Managerial Round

1. How do you balance data accuracy and reporting speed under tight deadlines?

2. Describe a time when your data recommendation was rejected — what did you learn?

3. How do you collaborate with medical and non-technical stakeholders?

✨ Pro Tip:

Eli Lilly focuses on data integrity, reproducibility, and domain-driven insights.

If you can combine technical expertise with healthcare understanding, you’ll stand out.

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Comments (0)

📚 Chapters

Eli Lilly Senior Data Analyst Interview EXP

Eli Lilly Senior Data Analyst Interview Experience (CTC – ₹22 LPA)

One of my friends recently appeared for Eli Lilly’s Senior Data Analyst role — and the interview process was a perfect blend of data engineering, analytics, and domain-focused problem-solving. Here’s how the rounds unfolded

Round 1: SQL (Technical Assessment)

Eli Lilly focuses heavily on complex joins, subqueries, and analytics on healthcare datasets.

Some questions included:

Round 2: Python + Data Cleaning Case

1. Given a messy CSV with nulls, outliers, and inconsistent date formats — clean and standardize it using pandas. 2. Derive meaningful KPIs such as Average Prescription per Doctor and Total Active Patients. 3. How would you automate data validation in a production pipeline?

Round 3: Tableau + Storytelling

1. Create a visualization for prescription patterns across age groups and regions. 2. Build a dashboard showing treatment adherence rates and highlight insights for leadership. 3. How do you ensure clinical data confidentiality while visualizing trends?

Round 4: Business Case + Domain Understanding

1. The sales team reports a drop in insulin drug revenue. How will you identify the cause? 2. What KPIs would you define for patient retention programs? 3. How would you measure the success of a new drug launch campaign?

Round 5: Managerial Round

1. How do you balance data accuracy and reporting speed under tight deadlines? 2. Describe a time when your data recommendation was rejected — what did you learn? 3. How do you collaborate with medical and non-technical stakeholders?

✨ Pro Tip:

Eli Lilly focuses on data integrity, reproducibility, and domain-driven insights. If you can combine technical expertise with healthcare understanding, you’ll stand out.

💬 Comments

Comments (0)

One of my friends recently appeared for Eli Lilly’s Senior Data Analyst role — and the interview process was a perfect blend of data engineering, analytics, and domain-focused problem-solving.
Here’s how the rounds unfolded

1. Given a messy CSV with nulls, outliers, and inconsistent date formats — clean and standardize it using pandas.

2. Derive meaningful KPIs such as Average Prescription per Doctor and Total Active Patients.

3. How would you automate data validation in a production pipeline?

1. Create a visualization for prescription patterns across age groups and regions.

2. Build a dashboard showing treatment adherence rates and highlight insights for leadership.

3. How do you ensure clinical data confidentiality while visualizing trends?

1. The sales team reports a drop in insulin drug revenue. How will you identify the cause?

2. What KPIs would you define for patient retention programs?

3. How would you measure the success of a new drug launch campaign?

1. How do you balance data accuracy and reporting speed under tight deadlines?

2. Describe a time when your data recommendation was rejected — what did you learn?

3. How do you collaborate with medical and non-technical stakeholders?

Eli Lilly focuses on data integrity, reproducibility, and domain-driven insights.

If you can combine technical expertise with healthcare understanding, you’ll stand out.