Citi Hiring Data Science Analyst (Bengaluru) | ₹8–15 LPA

Job Overview

The Spec Analytics Analyst is an entry-level trainee role within the data science and analytics function. The position requires a working knowledge of processes, systems, and procedures used to complete assigned tasks, along with a basic understanding of the principles behind them. The analyst collaborates with team members and supports business objectives through data-driven insights.

The role involves evaluating factual information, applying analytical techniques, and resolving problems using established approaches and technical knowledge. The impact of this role is limited to the quality and accuracy of the tasks performed, contributing to the broader work of the analytics team.

Key Responsibilities

• Data Collection and Cleaning: Support the collection, cleaning, and preprocessing of large datasets to maintain data quality and integrity.
• Exploratory Data Analysis: Perform basic exploratory data analysis to uncover patterns, trends, and insights within datasets.
• Feature Engineering Support: Assist in identifying and creating features used for machine learning models.
• Model Development Assistance: Help build, train, and evaluate basic machine learning models under the supervision of senior team members.
• Documentation: Maintain clear documentation for data pipelines, analytical processes, models, and outcomes.
• Collaboration: Work with data scientists, engineers, and business stakeholders to support analytics initiatives.
• Learning and Development: Participate in training programs, workshops, and independent learning to strengthen data science capabilities.
• Reporting: Prepare reports, dashboards, and visualizations that communicate analytical findings effectively.

Technical Work Areas

• Development of advanced search techniques, including semantic search.
• Building solutions using Retrieval-Augmented Generation (RAG) frameworks for generative AI applications.
• Development of agent-based solutions using frameworks such as LangChain or Google Agent Space.

Qualifications

Education

Bachelor's or Master's degree in a quantitative discipline such as Computer Science, Statistics, Mathematics, Economics, Engineering, or a related field.

Technical Skills

• Programming knowledge in Python (Pandas, NumPy, Scikit-learn) or R.
• Basic SQL skills for querying and manipulating data.
• Understanding of statistical concepts including regression and hypothesis testing.
• Familiarity with visualization tools or libraries such as Matplotlib, Seaborn, Tableau, or Power BI.
• Conceptual understanding of machine learning algorithms such as Linear Regression, Logistic Regression, and Decision Trees.

Preferred Exposure

• Version control tools such as Git.
• Cloud platforms including AWS, Azure, or GCP.
• Big data technologies such as Spark or Hadoop.
• Participation in data science courses, bootcamps, personal projects, or Kaggle competitions.

What the Role Offers

• Structured mentorship with experienced data scientists.
• Continuous learning and professional development opportunities.
• Exposure to real-world datasets and analytics challenges.
• A collaborative and innovative work environment.
• Potential progression into a full Data Scientist role upon successful completion of the trainee program.