Data Scientist

Amgen; Hyderabad; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Amgen is seeking a Data Scientist, Forecasting to join the Forecasting team within the AI & Data organization in Hyderabad. You will develop statistical, Bayesian, and machine learning models to improve forecasting and quantify uncertainty for business decisions.

You will collaborate with cross-functional teams, work on time-series forecasting across planning horizons, and communicate insights to stakeholders.

Qualifications

• 4+ years of experience applying data science, analytics, or statistical modeling in industry, research, or enterprise environments.
• Proficiency in time-series forecasting, predictive modeling, or related quantitative methods.
• Proficiency in Python and SQL, with experience using data science libraries such as scikit-learn, PyMC, PyTorch, TensorFlow, or similar.

Responsibilities

• Develop and refine statistical, Bayesian, and machine learning models to support demand forecasting across near-, medium-, and long-term planning horizons.
• Analyze large, complex datasets using statistical modeling, forecasting, and analytics techniques to generate insights that support business decision-making.
• Support the development of simulation and scenario-analysis capabilities to understand dynamics among patients, payers, providers, and market conditions.
• Collaborate with senior team members to evaluate and apply new tools and methodologies in forecasting, data science, and AI to business problems.

Skills

Time-series forecasting

Predictive modeling

Python

SQL

Statistical analysis

Communication

Collaboration

Tools

scikit-learn

PyMC

PyTorch

TensorFlow

Job description

## Data ScientistApply: On Site: India - Hyderabad: Full time: Posted Today: R-251196## **Career Category**Engineering## ## **Job Description****ABOUT THE ROLE**We are seeking a Data Scientist, Forecasting to join the Forecasting team within the AI & Data organization. This role will support the development of statistical, Bayesian, causal, and machine learning models that enhance forecasting capabilities and quantify uncertainty to guide decision-making across the company.This role will work cross-functionally to help build forecasting solutions that support critical business processes and contribute to Amgen’s “every patient, every time” mandate. The position is well suited to a curious and collaborative problem solver who is excited about applying forecasting methods, complex datasets, and modern analytical tools to build decision-support solutions that inform planning and business decision-making.**Key Responsibilities*** Develop and refine statistical, Bayesian, and machine learning models to support demand forecasting across near-, medium-, and long-term planning horizons.* Analyze large, complex datasets using statistical modeling, forecasting, and analytics techniques to generate insights that support business decision-making.* Support the development of simulation and scenario-analysis capabilities to better understand dynamics among patients, payers, providers, and market conditions.* Contribute across the modeling lifecycle, including business problem framing, exploratory data analysis, feature engineering, model development, validation, deployment support, monitoring, and explainability.* Collaborate with senior team members to evaluate and apply new tools and methodologies in forecasting, data science, and AI to business problems.* Communicate analytical findings and model results clearly to technical and non-technical stakeholders.**Basic Qualifications*** 4+ years of experience applying data science, analytics, or statistical modeling in industry, research, or enterprise environments.* Experience with time-series forecasting, predictive modeling, or related quantitative methods.* Proficiency in Python and SQL, with experience using tools such as scikit-learn, PyMC, PyTorch, TensorFlow, or similar data science libraries.* Solid analytical and statistical foundation, with the ability to work with messy and complex datasets to generate actionable insights.* Familiarity with model development workflows, including data preparation, feature engineering, evaluation, and interpretation.* Strong communication skills, with the ability to explain technical concepts and results to a range of stakeholders.* Strong collaboration skills and ability to work effectively in cross-functional environments.* Intellectual curiosity and a willingness to learn, take on ambiguous problems, and grow in a fast-paced environment**Preferred Qualifications*** Experience applying machine learning, statistical modeling, or decision science methods in retail, consumer goods, supply chain, manufacturing, or similar settings.* Exposure to causal inference, probabilistic modeling, or scenario analysis is a plus.