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Dun & Bradstreet is hiring for an FRESHER entry level Data Science Intern role in India




Position:

• Intern, Data Science

Company:

• Dun & Bradstreet

Location:

• Chennai, Tamil Nadu, India

Job Type:

• Internship

Job Mode:

• Onsite

Job Requisition ID:

• R-19011

Years of Experience:

• Freshers
• 2025 Graduates
• 0 Years of Experience

Company Description

• Dun & Bradstreet is a globally recognized organization specializing in business intelligence, commercial data, analytics, and decision support solutions. The company has built a strong reputation over many decades by helping businesses make informed decisions through trusted data, advanced analytics, and actionable insights.

• Founded in 1841, the organization has evolved into one of the world's leading providers of business information and analytics services. Its solutions help organizations understand customers, suppliers, partners, and markets while reducing uncertainty in strategic and operational decision making.

• With operations spanning numerous countries and industries, the company serves businesses of all sizes, from startups and small enterprises to multinational corporations. Its extensive data ecosystem powers a wide range of products and services focused on risk management, customer intelligence, compliance, sales acceleration, and business growth.

• The organization continuously invests in innovation, data science, artificial intelligence, machine learning, and cloud technologies to provide clients with advanced business insights. Through its Data Cloud and analytical capabilities, the company enables customers to identify opportunities, minimize risks, improve operational efficiency, and achieve sustainable growth.

• Employees at Dun & Bradstreet have opportunities to work on large scale datasets, modern analytics platforms, and cutting edge technologies while collaborating with talented professionals across multiple domains. The company's culture encourages continuous learning, innovation, professional development, and knowledge sharing.

• As a trusted leader in information services, the organization remains committed to helping businesses transform data into strategic intelligence that drives measurable business outcomes and long term success.

Profile Overview

• The Data Science Intern position offers an excellent opportunity for recent graduates to begin their professional journey within a globally respected analytics organization.

• This internship is designed for individuals who have a strong interest in data science, analytics, machine learning, statistics, and programming. The role provides exposure to real business challenges and allows candidates to work with large scale datasets while learning industry best practices.

• Interns will participate in various stages of analytical solution development, including data extraction, preprocessing, exploration, model development, validation, implementation, monitoring, and reporting. This hands on experience helps build a strong foundation in practical data science applications.

• The role provides opportunities to work with technologies such as Python, PySpark, Databricks, SQL, and other modern data processing platforms. Candidates will gain exposure to enterprise grade data environments and advanced analytics workflows.

• Successful interns will collaborate with experienced data scientists, analysts, engineers, and business stakeholders. Through these interactions, they will learn how analytical insights are developed and translated into business value.

• The internship also introduces participants to machine learning methodologies, natural language processing techniques, and analytical frameworks that support decision making across various business functions.

• Candidates who enjoy problem solving, working with data, identifying patterns, and generating insights will find this role highly rewarding. The position provides valuable industry exposure and helps establish a strong foundation for future careers in data science, analytics, artificial intelligence, and related fields.

Key Responsibilities

Data Collection and Data Extraction

• Gather and retrieve large volumes of structured and unstructured data from multiple internal and external data sources.

• Utilize modern tools and technologies such as Python, PySpark, SQL, and Databricks to efficiently extract and process information.

• Ensure data quality, consistency, and accuracy during data acquisition activities.

• Support the preparation of datasets required for analytical and machine learning initiatives.

Data Processing and Analysis

• Analyze large datasets to identify patterns, trends, anomalies, and business opportunities.

• Perform exploratory data analysis to understand data characteristics and generate meaningful observations.

• Assist in transforming raw information into clean, usable datasets for downstream analytics.

• Apply statistical methods to derive insights and support business recommendations.

Analytical Solution Development

• Participate in designing analytical frameworks that address business challenges.

• Assist in the development and implementation of analytical models and reporting solutions.

• Contribute to validation, calibration, testing, and monitoring activities associated with analytical projects.

• Help maintain documentation for analytical methodologies, assumptions, processes, and outcomes.

Machine Learning and Advanced Analytics

• Gain exposure to supervised and unsupervised machine learning techniques.

• Support projects involving classification, clustering, prediction, segmentation, and pattern recognition.

• Learn how machine learning models are developed, evaluated, and deployed in production environments.

• Participate in initiatives involving natural language processing and emerging analytical technologies.

Reporting and Business Insights

• Create reports and dashboards that communicate analytical findings effectively.

• Translate technical outputs into business friendly insights.

• Support stakeholders by presenting observations and recommendations derived from data.

• Assist in monitoring performance metrics and reporting project outcomes.

Collaboration and Learning

• Work closely with experienced professionals across data science and analytics teams.

• Participate in knowledge sharing sessions, team discussions, and project reviews.

• Continuously learn new tools, methodologies, and analytical techniques.

• Develop professional skills related to communication, teamwork, and problem solving.

Qualifications

• Bachelor's or equivalent degree completed in 2025.

• Educational background in Computer Science, Data Science, Statistics, Mathematics, Engineering, Information Technology, Analytics, or related disciplines.

• Strong interest in pursuing a career in data science, analytics, machine learning, or artificial intelligence.

• Familiarity with programming concepts and software development fundamentals.

• Understanding of Python programming language and its analytical ecosystem.

• Exposure to libraries and tools commonly used for data analysis and machine learning is advantageous.

• Basic understanding of SQL and database concepts.

• Knowledge of statistical methods and their practical applications.

• Ability to understand data patterns and derive meaningful conclusions.

• Strong analytical thinking and structured problem solving abilities.

• Ability to work with numerical information and interpret complex datasets.

• Good written and verbal communication skills in English.

• Ability to communicate findings clearly and professionally.

• Strong willingness to learn new technologies and adapt to changing business requirements.

• Self motivated attitude with a commitment to continuous improvement.

• Ability to collaborate effectively within cross functional teams.

• Attention to detail and commitment to delivering quality work.

• Understanding of machine learning concepts, even at an academic level, would be beneficial.

• Exposure to data visualization techniques and reporting tools may be advantageous.

Skills Preferred

Programming Skills

• Python

• PySpark

• SQL

• Databricks

• Data Manipulation

• Data Processing

Data Science Skills

• Statistical Analysis

• Data Exploration

• Predictive Analytics

• Machine Learning Fundamentals

• Data Validation

• Data Quality Assessment

Soft Skills

• Communication

• Problem Solving

• Critical Thinking

• Team Collaboration

• Presentation Skills

• Time Management

• Learning Agility

Technical Exposure

• Supervised Learning

• Unsupervised Learning

• Natural Language Processing

• Data Engineering Concepts

• Reporting and Documentation

• Analytical Solution Development

Additional Information

• This internship provides valuable exposure to real world data science projects within a globally recognized organization.

• Selected candidates will have the opportunity to learn from experienced professionals working on enterprise scale analytics initiatives.

• The role offers practical experience with industry standard technologies and modern data platforms.

• Interns will gain understanding of the complete analytical lifecycle, from data acquisition through insight generation and reporting.

• The position helps participants develop both technical and business skills required for successful careers in analytics and data science.

• Exposure to machine learning, statistical modeling, and advanced analytics can significantly strengthen a candidate's professional profile.

• The organization promotes a culture of continuous learning and encourages employees to enhance their knowledge and technical expertise.

• Candidates will learn how data driven decisions are made within large organizations and how analytics supports business growth.

• The company may utilize AI assisted tools during parts of the recruitment process, including resume review and application assessment. However, final hiring decisions remain under human oversight.

• This opportunity is ideal for fresh graduates seeking hands on industry experience and looking to build a strong foundation in data science and analytics.

• Strong performers may gain valuable industry connections, practical project experience, and enhanced career prospects within the analytics domain.

• The internship serves as an excellent stepping stone toward future roles in data science, business analytics, machine learning, artificial intelligence, and data engineering.


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