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채용Amgen

Associate Data Scientist (BI - Reporting)

Amgen

Associate Data Scientist (BI - Reporting)

Amgen

India - Hyderabad

·

On-site

·

Full-time

·

1w ago

Career Category

Information Systems:

Job Description Level:

Associate (L3)Role: BI Reporting – MSO Ops

MIO OVERVIEW:

T The Marketing Science Operations (MSO) vertical at Amgen is the operational backbone that ensures accurate, timely, governed, and analytics ready marketing data across all digital channels. MSO enables the MIO (Marketing Investment & Optimization), and broader Decision Sciences teams to run self-service analytics, generate insights, and execute campaigns reliably.

MSO focuses on data readiness, governance, pipeline operations, vendor accountability, and automation with the goal of delivering clean, standardized, and insight-ready datasets.

Role Summary

The Associate – MSO BI Reporting role is entry level analytics and reporting position within the Marketing Science Operations (MSO) BI team. This role is ideal for candidates who are interested in building strong foundations in business intelligence, reporting, and data quality.

The team will provide structured learning and on‑the‑job exposure. What matters most is curiosity, critical thinking, and a strong learning mindset.

LIVE | WHAT YOU WILL DO

As an MSO BI Reporting Associate, you will work under the guidance of Senior Associates and Managers to support BI reporting, dashboarding, and data quality operations.

You will:

  • Support development and maintenance of standard BI dashboards and reports.
  • Perform data validation, reconciliation, and QA checks to ensure accuracy and consistency.
  • Assist in data extraction, transformation, and preparation for reporting use cases.
  • Monitor data refreshes, pipeline health, and reporting completeness.
  • Help document metric definitions, data sources, and reporting logic.
  • Support regular weekly and monthly reporting cycles.
  • Identify data issues, anomalies, or gaps and escalate appropriately**;** Closely collaborate with Data Engineering stakeholders.

BASIC QUALIFICATIONS

  • Bachelor's (3 to 6 Yrs) or master's (2 to 4 Yrs) degree required in any discipline with strong record of academic success in quantitative and analytic coursework such as operations research, applied mathematics, management science, data science, statistics, econometrics, or engineering.

  • Experience in Tableau, Power BI, or similar visualization tools; Familiarity with dashboards, KPIs, or recurring reports

  • Effective oral and written communication skills.

  • Comfort working with structured data, tables, and reports.

Preferred Qualifications

  • Basic experience with Excel, SQL, or any BI/reporting tool
  • Interest in data governance, reporting standards, or analytics operations.
  • Experience supporting analytics in pharma, healthcare, or regulated environments.
  • Effective communication skills with the ability to collaborate closely with Senior Associates to deliver high‑quality analytical outputs.
  • Exposure to Dev Sec Ops practice
  • Exposure to Incident Management

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총 조회수

0

총 지원 클릭 수

0

모의 지원자 수

0

스크랩

0

Amgen 소개

Amgen

Amgen

Public

A biotechnology company that develops and manufactures human therapeutics for various illnesses and diseases.

10,001+

직원 수

Thousand Oaks

본사 위치

$138B

기업 가치

리뷰

3.6

10개 리뷰

워라밸

3.2

보상

4.1

문화

3.4

커리어

2.8

경영진

3.5

65%

친구에게 추천

장점

Excellent benefits and health benefits

Good pay and compensation

Supportive management and strong leadership

단점

Limited career growth and promotion opportunities

Work-life balance challenges and long hours

Bureaucratic processes

연봉 정보

1,244개 데이터

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Data Scientist

0개 리포트

$100,368

총 연봉

기본급

-

주식

-

보너스

-

$85,234

$115,502

면접 경험

5개 면접

난이도

3.0

/ 5

소요 기간

14-28주

합격률

40%

경험

긍정 20%

보통 80%

부정 0%

면접 과정

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

Technical/Role-Specific Interview

5

Panel Interview

6

Offer

자주 나오는 질문

Technical Knowledge

Behavioral/STAR

Past Experience

Data Analysis/Statistics

Culture Fit