Associate Data Scientist

About the Role

The Associate Data Scientist role is a core contributor within the Enterprise Data & Analytics team, responsible for solving well-defined analytical and machine learning problems through strong technical execution.

You will work closely with senior data scientists and data engineers to support the development, validation, and implementation of models across use cases.

Key Responsibilities

• Develop, test, and implement statistical and machine learning models under guidance from senior team members.
• Apply standard techniques such as regression, classification, clustering, and forecasting to pre-defined problem statements.
• Ensure models are reliable, interpretable, and aligned with defined objectives.
• Work on clearly defined analytical problem statements provided by senior team members.
• Support hypothesis testing, feature engineering, and structured analysis under guidance.

Skills & Qualifications

• Bachelor's Degree in Data Science, Statistics, Mathematics, Computer Science, or related field.
• Basic proficiency in Python, R, or similar analytical programming languages.
• Foundational understanding of statistics and machine learning.
• Strong attention to detail and focus on accuracy.
• Structured thinking and problem-solving approach.
• Basic understanding of model evaluation and interpretation concepts.
• Commitment to high professional and ethical standards.

What You'll Learn

As an Associate Data Scientist, you will gain exposure to structured and unstructured data, including NLP and LLM-based techniques.

You will work closely with senior data scientists and data engineers to develop and implement models across use cases.

This role will provide a foundation for developing more advanced analytical and problem-solving capabilities.

Resume Tip

When applying for this role, be sure to highlight any academic or internship experience in analytics/data science, as well as any relevant projects or coursework that demonstrate your skills in data analysis and machine learning.

Emphasize your ability to work with structured and unstructured data, and highlight any experience with NLP and LLM-based techniques.

Use specific examples to demonstrate your problem-solving approach and attention to detail.