Sr Associate Data Scientist

Amgen Inc; Hyderabad; On-site; INR 1,000,000 - 1,500,000; Full time

Job summary

Amgen Inc is hiring a Data Scientist in Hyderabad, India to develop AI-driven solutions for enhancing cybersecurity. The successful candidate will analyze security data, detect threats, and implement data-driven automation. Candidates should have a Master's or Bachelor's degree with 3-5 years of experience in analytics, specifically with tools like Python, SAS, and SPSS. Strong analytical skills and teamwork are essential for collaborating with cybersecurity teams and developing impactful solutions.

Qualifications

• Masters or Bachelors degree with 3-5 years of experience in analytics tools.
• Strong background in machine learning algorithms and techniques.
• Experience with statistical techniques and hypothesis testing.

Responsibilities

• Develop analytics to enhance organizational security.
• Collaborate with data engineers on security-focused analytics.
• Generate reports and document your work.

Skills

Python

Data analysis

Machine learning

Problem-solving

Education

Masters or Bachelor's degree in a relevant field

Tools

SAS

SPSS

R

Python

AWS

Azure

Google Cloud

Databricks

TensorFlow

PyTorch

Scikit-learn

Job description

About the Role

Role Description: The Data Scientist is responsible for developing and implementing AI‑driven solutions to enhance cybersecurity measures within the organization. This role involves leveraging data science techniques to analyze security data, detect threats, and enhance security processes with generative AI and other analytic capabilities. The Data Scientist will work closely with cybersecurity teams to identify data‑driven automation opportunities which strengthen the organization’s security posture.

Roles Responsibilities

• Develop analytics to address security concerns, enhancements, and capabilities to improve the organization’s security posture.
• Collaborate with Data Engineers to translate security‑focused algorithms into effective solutions.
• Work in technical teams in development, deployment, and application of applied analytics, predictive analytics, and prescriptive analytics.
• Perform exploratory and targeted data analyses using descriptive statistics and other methods to identify security patterns and anomalies.
• Design and implement security‑focused analytics pipelines leveraging MLOps practices, generative AI, and agent‑based architectures (e.g., autonomous agents for threat detection and response).
• Collaborate with data engineers on data quality assessment, data cleansing, and the development of security‑related data pipelines.
• Contribute to data engineering efforts to refine data infrastructure and ensure scalable, efficient security analytics.
• Generate reports, annotated code, and other project artifacts to document, archive, and communicate your work and outcomes.
• Share and discuss findings with team members practicing SAFe Agile delivery model.

Functional Skills: Basic Qualifications

• Masters degree OR Bachelors degree and 3 to 5 years of experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python)

Preferred Qualifications

• Experience with one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python)
• Experience applying generative AI and agent‑based systems to cybersecurity use cases (e.g., automated threat detection, response orchestration, and security analysis)
• Demonstrated skill in the use of applied analytics, descriptive statistics, feature extraction and predictive analytics on industrial datasets
• Strong foundation in machine learning algorithms and techniques
• Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification

Good‑to‑Have Skills

• Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit‑learn)
• Outstanding analytical and problem‑solving skills; ability to learn quickly; excellent communication and interpersonal skills
• Experience with data engineering and pipeline development
• Experience in analyzing time‑series data for forecasting and trend analysis
• Experience with AWS, Azure, or Google Cloud
• Experience with Databricks platform for data analytics and MLOps
• Experience working in Product teams