Associate Data Scientist

**Associate**Data Scientist** - Forecasting**

**Role Name**:Associate**Data**Scientist**:

- Forecasting**

**Department Name**:AI & Data Science

**Role GCF**:3

**Hiring Manager Name**:Monsu Mathew

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:
You will manipulate large messy datasets, write high-quality code, and adapt complicated machine learning models to the problems at-hand. The Associate Data Scientist should be familiar with moving models from development to production and have a good sense for tracking and updating model performance.

Roles & Responsibilities:

- ** Integ**ral part of a** high performing team**of data scientists and engineers looking to translate machine learning algorithms into effective solutions focused on forecasting
- ** Perform exploratory and targeted data analyses** using descriptive statistics and other methods to identify patterns and anomalies
- ** Assist** in d**evelop**ment of** high-performance**forecasting**algorithms**, prototypes, predictive models, and proof of concepts using a cutting-edge technical stack
- ** Develop** analytics pipelines leveraging MLOps practices
- ** Collaborate with data engineers** on data quality assessment, data cleansing, and the development of operational data pipelines
- ** 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
- ** Assuring compliance with regulatory, security, and privacy requirements** as it relates to data assets
- ** Share and discuss findings** with team members and stakeholders

Must-Have Skills:

- Experience in analyzing time-series data for forecasting and trend analysis
- Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)
- Understanding of the modern data stack: distributed computing tools (Spark, Hive, etc.), cloud computing environments, and source code control technologies (e.g. Git)
- Familiar with state-of-the-art machine learning tools, such as deep learning frameworks, transformer models, NLP models, and time series models, with demonstrated and interpretable insight and impact
- Strong communication skills - capable of presenting complicated and nuanced work in a clear, concise, and understandable manner to a diverse audience

Nice-to-Have Skills:

- Experience in Biotechnology or pharma industry is a big plus
- Foundation in machine learning algorithms and techniques

Education and Professional Certifications
- Master’s degree or Bachelor’s degree in Computer Science, Business, Engineering, IT or related field
- 2+ Years of relevant work experience
- Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus

Soft Skills:

- Initiative to explore alternate technology and approaches to solving problems
- Skilled in breaking down problems, documenting problem statements, and estimating efforts
- Excellent analytical and troubleshooting skills
- Strong verbal and written communication skills
- Ability to work effectively with global, virtual teams
- High degree of initiative and self-motivation
- Ability to manage multiple priorities successfully
- Team-oriented, with a focus on achieving team goals
- Ability to learn quickly, be organized and detail oriented
- Strong presentation and public speaking skills

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.