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求人Amgen

Specialist IS Data Scientist - Finance

Amgen

Specialist IS Data Scientist - Finance

Amgen

India - Hyderabad

·

On-site

·

Full-time

·

1mo ago

必須スキル

Python

Machine Learning

NLP

GenAI

PySpark

Scala

Databricks

Prompt Engineering

Statistical Modeling

Career Category

Information Systems:

Job Description

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world’s toughest diseases, and make people’s lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what’s known today.

ABOUT THE ROLE

Role Description:

Let’s do this. Let’s change the world. In this vital role you will leverage advanced analytics, AI, and GenAI capabilities to unlock insights and drive innovation in Amgen’s finance landscape. You will be an integral member of a dynamic product team that builds and deploys financial planning and AI-driven solutions, harnessing Finance data from Amgen’s enterprise data lake. If you are a passionate data scientist with a track record of applying AI/ML to real-world business problems—and you want to influence how a leading biotech company uses its data—this is the role for you!

Roles & Responsibilities:

  • Collaborate with Finance stakeholders to identify and prioritize high-value AI/ML and GenAI use cases that deliver measurable business value.
  • Develop, train, validate, and deploy machine learning, natural language processing (NLP), and GenAI models to solve finance-specific problems such as forecasting, scenario modeling, anomaly detection, and intelligent automation.
  • Partner with data engineering teams to access and prepare curated datasets from Amgen’s enterprise data lake for advanced analytics.
  • Apply prompt engineering and fine-tuning techniques to adapt large language models (LLMs).
  • Create and maintain AI/ML solution documentation, including methodology, model interpretability, and compliance considerations in a regulated environment.
  • Establish and promote best practices for responsible AI, model governance, and ethical use of AI in Finance.
  • Stay current with industry trends and emerging technologies in AI, GenAI, and advanced analytics, and assess their applicability to Amgen Finance.

Basic Qualifications and Experience:

  • Master’s/ Bachelor’s degree and 8 to 14 years of Computer Science, IT or related field experience.

Functional Skills:

Must-Have Skills:

  • Strong proficiency in Python for data analysis, ML, and AI development (Pandas, Num Py, scikit-learn, Tensor Flow, Py Torch).
  • Hands-on experience with large language models (LLMs), prompt engineering, and fine-tuning using frameworks like Hugging Face Transformers.
  • Expertise building machine learning workflows for forecasting and statistical modeling.
  • Experience with GenAI APIs (e.g., OpenAI, Azure OpenAI, Anthropic Claude) and vector databases (e.g., Pinecone, FAISS) for retrieval-augmented generation (RAG).
  • Proficiency in Python, Py Spark, and Scala for data processing, with hands-on experience in using Databricks for building ETL pipelines and handling big data processing
  • Experience with data warehousing platforms such as Amazon Redshift, or Snowflake.
  • Proven ability to translate business problems into technical solutions, with measurable outcomes.

Good-to-Have Skills:

  • Experience applying AI to Finance-related domains (forecasting, planning).
  • Familiarity with visualization tools (Tableau, Power BI) for presenting AI-driven insights.
  • Understanding of DevOps tools and practices for continuous integration/continuous deployment (CI/CD) of ML models.
  • Familiarity with Enterprise Performance Management (EPM) solutions like Anaplan, Hyperion, SAP Analytics Cloud Planning

Professional Certifications:

  • AWS Certified Machine Learning – Specialty (preferred)
  • Databricks Certified Machine Learning Professional (preferred)

Soft Skills:

  • Excellent critical-thinking and problem-solving skills
  • Strong collaboration and communication abilities, with the ability to explain AI concepts to non-technical audiences
  • Self-motivated with a high degree of initiative
  • Ability to manage multiple priorities in a fast-paced, dynamic environment
  • Comfortable working in an Agile environment and contributing to continuous delivery cycles

Shift Information:

This position requires you to work a later shift and may be assigned a second or third shift schedule. Candidates must be willing and able to work during evening or night shifts, as required based on business requirements.

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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Amgenについて

Amgen

Amgen

Public

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

10,001+

従業員数

Thousand Oaks

本社所在地

$138B

企業価値

レビュー

3.6

10件のレビュー

ワークライフバランス

3.2

報酬

4.1

企業文化

3.4

キャリア

2.8

経営陣

3.5

65%

友人に勧める

良い点

Excellent benefits and health benefits

Good pay and compensation

Supportive management and strong leadership

改善点

Limited career growth and promotion opportunities

Work-life balance challenges and long hours

Bureaucratic processes

給与レンジ

1,244件のデータ

Junior/L3

L2

L3

L4

L5

L6

M3

M4

M5

M6

Mid/L4

Senior/L5

Staff/L6

Junior/L3 · Data Scientist

0件のレポート

$100,368

年収総額

基本給

-

ストック

-

ボーナス

-

$85,234

$115,502

面接体験

5件の面接

難易度

3.0

/ 5

期間

14-28週間

内定率

40%

体験

ポジティブ 20%

普通 80%

ネガティブ 0%

面接プロセス

1

Application Review

2

HR Screen

3

Hiring Manager Interview

4

Technical/Role-Specific Interview

5

Panel Interview

6

Offer

よくある質問

Technical Knowledge

Behavioral/STAR

Past Experience

Data Analysis/Statistics

Culture Fit