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:
The role is responsible for designing, building, maintaining, analyzing, and interpreting data to provide actionable insights that drive business decisions. This role involves working with large datasets, developing reports, supporting and executing data governance initiatives and, visualizing data to ensure data is accessible, reliable, and efficiently managed. The ideal candidate has strong technical skills, experience with big data technologies, and a deep understanding of data architecture and ETL processes
Roles & Responsibilities:
Design, develop, and maintain data solutions for data generation, collection, and processing
Be a key team member that assists in design and development of the data pipeline
Create data pipelines and ensure data quality by implementing ETL processes to migrate and deploy data across systems
Contribute to the design, development, and implementation of data pipelines, ETL/ELT processes, and data integration solutions
Take ownership of data pipeline projects from inception to deployment, manage scope, timelines, and risks
Collaborate with cross-functional teams to understand data requirements and design solutions that meet business needs
Develop and maintain data models, data dictionaries, and other documentation to ensure data accuracy and consistency
Implement data security and privacy measures to protect sensitive data
Leverage cloud platforms (AWS preferred) to build scalable and efficient data solutions
Collaborate and communicate effectively with product teams
Collaborate with site & network to analyze and select appropriate data models & algorithms that focus on gaining data insights to improve business process or value
Design, write, and test data / ML pipelines / LLM and other advanced analytic / visualization or AI solutions.
Prioritize & lead the implementation of internally developed and externally provided analytic solutions.
Coordinate & project manage the delivery / development of data / ML pipelines / LLM and other advanced analytic / visualization or AI solutions.
Collect business requirements / user stories for new or enhancements to existing analytic solutions.
Translate business requirement / pain point to Machine Learning use case to resolve real world business problems
Implement most recent algorithms and approaches for machine learning
Initiates and participates in projects in prediction, optimization, and processes using advanced Deep Learning / Statistical / Mathematical approach
Provide technical oversight and guidance to other Data Analytics team members.
Basic Qualifications and Experience:
Bachelor’s degree with 8 - 12 years of experience in Computer Science, IT or related field
Bachelor’s or Master's Degree in Computer Science, Software Engineering, Data Science , Statistics or similar field OR
Bachelor's Degree and 8 years of Engineering or Scientific experience
Functional Skills:
Must-Have Skills (Not more than 3 to 4):
Hands-on experience with big data technologies and platforms, such as Databricks, Apache Spark (PySpark, SparkSQL), workflow orchestration, performance tuning on big data processing
Hands on experience with various Python/R packages for EDA, feature engineering and machine learning model training
Proficiency in data analysis tools (eg. SQL) and experience with data visualization tools, Tableu
Excellent problem-solving skills and the ability to work with large, complex datasets
Strong understanding of data governance frameworks, tools, and best practices.
Knowledge of data protection regulations and compliance requirements (e.g., GDPR, CCPA)
Proven project management skills and demonstrated ability to execute and manage complex projects and programs
A demonstrable ability to work in teams and serve as a technical mentor to junior team members
Agility and flexibility to adapt to changing priorities
Experience working effectively in a globally dispersed team environment
Good-to-Have Skills:
Experience with ETL tools such as Apache Spark, and various Python packages related to data processing, machine learning model development
Strong understanding of data modeling, data warehousing, and data integration concepts
Knowledge of Python/R, Databricks, SageMaker, cloud data platforms
Professional Certifications (please mention if the certification is preferred or mandatory for the role):
Certified Data Analyst (preferred on Databricks or cloud environments)
Certified Data Scientist (preferred on Databricks or Cloud environments)
Machine Learning Certification (preferred on Databricks or Cloud environments
Soft Skills:
Excellent critical-thinking and problem-solving skills
Strong communication and collaboration skills
Demonstrated awareness of how to function in a team setting
Demonstrated presentation skills
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 an accommodation.
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Salary: $45000-75000
🤖 This salary estimate is calculated by AI based on the job title, location, company, and market data. Use this as a guide for salary expectations or negotiations. The actual salary may vary based on your experience, qualifications, and company policies.
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