ROLES & RESPONSIBILITIES

Responsibilities will include, but are not limited to:
Data product and analytics solution delivery: Develop reusable analytics and data science solutions for supply chain, manufacturing, planning, logistics, clinical supply, and operations business challenges.
Data preparation and integration: Gather, clean, transform, and integrate data from multiple sources to create reliable datasets for analysis, modeling, visualization, feature engineering, and decision support.
Reusable analytical workflows: Build reproducible analytical workflows using Python, R, SQL, or similar tools, moving analyses beyond notebooks into maintainable, governed, and reusable solutions.
Cloud data platform analytics: Use platforms such as Databricks, Snowflake, or similar cloud data settings to prepare large datasets, develop scalable analytics, and support reusable analytical workflows.
Digital team partnership and data product translation: Partner closely with product owners, data engineers, platform teams, technology teams,



and business stakeholders to understand user needs, define analytical questions, translate needs into data product requirements, interpret results, and turn insights into action.
Analytics application enablement: Partner with technology teams to help deliver analytical and decision-support capabilities through contemporary application patterns, APIs, cloud deployment approaches, or web-based tools where appropriate.
Communication and decision translation: Communicate analytical methods, assumptions, findings, recommendations, uncertainty, and implementation tradeoffs clearly to technical and non-technical audiences.
Analytical excellence and continuous improvement: Promote solid analytical practices, including documentation, version control, testing, validation, reproducibility, reusable methods, technical curiosity, and continuous improvement.

PREFERRED QUALIFICATIONS

Preferred qualifications include:
Masters degree or PhD

📌 Ai Data Scientist Hyderabad
🏢 AMGEN
📍 Hyderabad