Data Science Analyst

Talent'd HR Solutions; Bengaluru; On-site; INR 600,000 - 1,000,000; Full time

Benefits offered by this job

Structured mentorship

Ongoing learning opportunities

Exposure to real-world datasets

Collaborative working environment

Competitive salary and benefits

Job summary

A leading analytics recruitment firm in Bengaluru is seeking a Trainee Analytics Analyst. This role focuses on data cleaning, exploratory analysis, and supporting machine learning model development while collaborating with experienced data scientists. The ideal candidate should have a degree in a quantitative field and foundational skills in Python and SQL. The position offers structured mentorship, professional development opportunities, and a path to a full Data Scientist role after the trainee program.

Qualifications

• Basic proficiency in Python (Pandas, NumPy, Scikit-learn) or R.
• Understanding of SQL for extracting and manipulating data.
• Knowledge of statistical concepts such as hypothesis testing and regression.
• Familiarity with tools or libraries for data visualization.

Responsibilities

• Assist with gathering, cleaning, and preprocessing large datasets.
• Perform basic exploratory data analysis to identify trends and insights.
• Support the building, training, and evaluation of basic machine learning models.
• Maintain clear documentation of data processes and analytical results.
• Work with senior data scientists and business stakeholders on analytical tasks.

Skills

Python

SQL

Statistics

Data Visualization

Machine Learning Fundamentals

Education

Bachelor's or Master's degree in a quantitative discipline

Tools

Tableau

Matplotlib

Seaborn

Job description

The Spec Analytics Analyst is a trainee-level role focused on supporting analytical initiatives. The position requires knowledge of common processes, procedures, and systems used to perform assigned tasks, along with a basic understanding of the concepts that guide the work. The role involves applying factual analysis to make evaluative judgments while working within established guidelines and precedents.

The analyst collaborates with team members and contributes to business outcomes through the quality of work delivered. The role has a limited but direct impact on business processes and focuses mainly on individual responsibilities within the team.

Key Responsibilities

• Data Collection and Cleaning: Assist with gathering, cleaning, and preprocessing large datasets to maintain accuracy and integrity.
• Exploratory Data Analysis: Perform basic exploratory data analysis to identify trends, patterns, and useful insights.
• Feature Engineering Support: Help create and select features that improve machine learning model performance.
• Model Development Assistance: Support the building, training, and evaluation of basic machine learning models under supervision.
• Documentation: Maintain clear documentation of data processes, analytical results, and model outputs.
• Collaboration: Work with senior data scientists, engineers, and business stakeholders to complete analytical tasks.
• Learning and Development: Participate in training programs, workshops, and self-learning activities to strengthen data science capabilities.
• Reporting: Assist in preparing reports and visualizations that communicate insights to stakeholders.

Qualifications

Education

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

Essential Technical Skills

• Programming: Basic proficiency in Python (Pandas, NumPy, Scikit-learn) or R.
• Database Skills: Understanding of SQL for extracting and manipulating data.
• Statistics: Knowledge of statistical concepts such as hypothesis testing and regression.
• Data Visualization: Familiarity with tools or libraries like Matplotlib, Seaborn, Tableau, or Power BI.
• Machine Learning Fundamentals: Conceptual knowledge of algorithms such as Linear Regression, Logistic Regression, and Decision Trees.

Preferred Qualifications

• Experience with version control systems such as Git.
• Exposure to cloud platforms like AWS, Azure, or GCP.
• Familiarity with big data technologies such as Spark or Hadoop.
• Participation in data science bootcamps, online courses, Kaggle competitions, or similar projects.

What We Offer

• Structured mentorship from experienced data scientists.
• Opportunities for ongoing learning and professional development.
• Exposure to real-world datasets and practical data science challenges.
• A collaborative and innovative working environment.
• Competitive salary and benefits.
• A potential pathway to a full Data Scientist role after successful completion of the trainee program.
• Work on advanced topics including semantic search techniques.
• Development of solutions using RAG frameworks for GenAI applications.
• Building agent-based solutions using frameworks such as LangChain and Google Agent Space.

Citi is an equal opportunity employer and considers qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected characteristic.