Data Scientist

Amgen

Data Scientist (CD&A) at Amgen working on advanced analytics and AI to solve business problems. Collaborating across teams to build analytics capabilities and insights in the biotech domain.

Posted 5/2/2026full-timeThousand Oaks • California, Illinois • 🇺🇸 United StatesJuniorMid-Level💰 $103,852 - $140,506 per yearWebsite

Tech Stack

Tools & technologies

CloudNumpyPandasPythonPyTorchScikit-LearnSparkSQLTensorflow

About the role

Key responsibilities & impact

Collaborate with business partners including commercial insights and analytics, brand teams, sales operations, data teams, external vendor partners, media agencies, service owners, and IS partners to create solutions and insights to solve challenging business problems across multiple therapeutic areas and commercial functions.
Apply deep technical expertise to manipulate large messy datasets, write high-quality code, and adapt complicated machine learning models to the problems at-hand.
Use and develop data science, machine learning, and artificial intelligence capabilities across Amgen’s commercial organization.
Transform business, medical, or scientific questions into analytical ones and map out solutions, delivery, and impact.
Identify business needs and propose potential analytical approaches for solutions.
Build high-performance algorithms, prototypes, predictive models, and proof of concepts using Python or R with reliable performance, interpretability, and action-ability.
Communicate cross-functionally with stakeholders to develop appropriate methodology to answer specific business questions.
Help further build the team by contributing ideas and standard methodologies and keeping abreast of developments in industry and academia.
Communicate effectively and influence a diverse set of technical, scientific, medical, and business constituents at the functional and executive levels.
Create powerful stories in PowerPoint, with knowledge of MS Office Suite (Excel and PowerPoint).
Assure compliance with regulatory, security, and privacy requirements as it relates to data assets.

Requirements

What you’ll need

Master’s degree OR Bachelor's degree and 2 years of experience in a quantitative field OR Associate’s degree and 6 years of experience in a quantitative field OR High school diploma / GED and 8 years of experience in a quantitative field
Experience in designing, evaluating, and applying a variety of supervised and unsupervised machine learning models to drive business value
Strong programming skills in Python, SQL, and/or R
Experience with data science and machine learning-related libraries in Python (Pandas, scikit-learn, TensorFlow, NumPy, PyTorch, MLib, etc)
Highly motivated with eagerness to learn and adapt to new subjects
Technical aptitude with strong logical, problem-solving, and decision-making skills
Excellent organization/planning skills and talent for managing many large and complex datasets
Ability to collaborate and influence business partners and other IS resources to drive analytic projects end-to-end
Ability to communicate analysis in a clear, precise, and impactful manner
Familiarity with the modern data stack: distributed computing tools (Spark, Hive, etc.), cloud computing environments, and source code control technologies (e.g. Git)
Passion for learning and staying on top of current developments in data science
Biotech / Pharma industry experience.

Benefits

Comp & perks

A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions
group medical, dental and vision coverage
life and disability insurance
flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

machine learningdata sciencePythonRSQLsupervised learningunsupervised learningalgorithm developmentpredictive modelingdata manipulation

Soft Skills

collaborationcommunicationproblem-solvingdecision-makingorganizationplanninginfluenceadaptabilitymotivationcreativity