• Collaborate with ML engineers and data platform teams to design, implement, and maintain the feature store architecture for both offline (batch) and online (real-time) use cases. • Identify, define, and engineer high-quality features from various raw data sources (databases, APIs, streaming data) using statistical analysis and domain knowledge. • Partner with database administrators, clinical experts, data scientists, ML engineers, and business stakeholders to promote feature reuse, define governance standards, track feature lineage, and ensure data consistency across models. • Build and optimize ingestion and transformation pipelines using distributed data frameworks to populate the feature store, ensuring data accuracy, reliability, and freshness. • Generate training and testing datasets from the feature store and work with ML engineers to ensure seamless feature serving for model inference in production environments. • Develop monitoring and alerting frameworks to track feature data quality, integrity, and latency, proactively identifying and resolving issues. • Document feature definitions, data sources, and usage best practices, and effectively communicate complex technical concepts and insights to technical and non-technical audiences.

• Gain hands-on experience in the biopharmaceutical industry during a 10 to 12-week program • Participate in team projects tied to strategic and tactical goals • Collaborate with cross-functional partners for data-driven solutions • Perform exploratory data analysis and communicate findings • Develop technical and analytical skills while providing insights

• Gain one of a kind hands-on experience to building a proven foundation for a career in the biopharmaceutical industry • Participate in one-week on-site visit in Thousand Oaks, CA with internship cohort • Collaborate with team members and cross-functional partners to deliver insights and data-driven solutions for business questions within predictive analytics, marketing investment optimization, and/or omnichannel marketing • Perform exploratory data analysis and data cleaning, build and evaluate machine learning models, create data visualizations and presentations, and communicate project findings to leadership and business partners • Develop professional, technical, and analytical skills while providing meaningful insights and recommendations for the business • Network with colleagues across the company, including full access to Amgen's Employee Resource Groups, networking/internship events, and an on-site visit to Amgen's headquarters in Thousand Oaks • Potential for full-time offer upon successful completion of program and performance evaluation

Company Description We are passionate people with an expert understanding of the digital consumer, data sciences, global telecom business, and emerging financial services. And we believe that we can make the world a better place. Job Description Looking for candidate making a career in Data Science with experience applying advanced statistics, data mining and machine learning algorithms to make data-driven predictions using programming languages like Python (including: Numpy, Pandas, Scikit-learn, Matplotlib, Seaborn), SQL (Postgresql). Experience with ElasticSearch, information/document retrieval, natural language processing is a plus. Experience with various machine learning methods (classification, clustering, natural language processing, ensemble methods, outlier analysis) and parameters that affect their performance also helps. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. Qualifications Qualifications ·         Bachelor's degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.) ·         At least 2 years' of experience in quantitative analytics or data modeling ·         Some understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms ·         Fluency in these programming languages (Python, SQL), Javascript/HTML/CSS/Web Development nice to have. ·         Familiarity with data science frameworks and visualization tools (Pandas, Visualizations (matplotlib, altair, etc), Jupyter Notebooks) Additional Information Responsibilities ·         Analyze raw data: assessing quality, cleansing, structuring for downstream processing ·         Design accurate and scalable prediction algorithms ·         Collaborate with engineering team to bring analytical prototypes to production ·         Generate actionable insights for business improvements tion will be kept confidential according to EEO guidelines.