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Dun & Bradstreet is hiring for an fresher entry level Data Scientist role in US




Position:

  • Data Scientist

Company:

  • Dun & Bradstreet

Location:

  • Florham Park, New Jersey, United States

Job type:

  • Full-time

Job mode:

  • On-site

Job requisition id:

  • R-17845

Years of experience:

  • Not explicitly required, but suited for entry-level to early-career professionals


Company Description

  • Dun & Bradstreet is a global leader in commercial data and analytics, committed to unlocking the power of data to help customers make confident business decisions.

  • The company has a history of over 180 years in delivering reliable data-driven insights to businesses worldwide.

  • With over 6,000 professionals globally, D&B’s team is passionate about innovation and focused on turning potential into prosperity.

  • The culture is award-winning, grounded in creativity, collaboration, and growth, welcoming individuals with bold, diverse thinking.

  • Employees are provided with opportunities to contribute to meaningful work, access continuous learning resources, and be part of a mission to drive global economic progress through better data.


Profile Overview:

  • The role of a Data Scientist at Dun & Bradstreet is deeply tied to solving practical business problems using advanced machine learning and data science techniques.

  • You will work on transforming complex business cases, both internal and from clients, into well-structured ML-based solutions.

  • The job involves identifying business needs independently, running multiple ML projects in parallel, and explaining results to both technical and non-technical stakeholders.

  • Collaboration across teams is key, but self-driven problem-solving and time management are equally important in the fast-paced environment.

  • There is a strong emphasis on continuous learning, sharing of knowledge, and applying the latest academic and industry research.


Qualifications:

  • A bachelor’s degree is required, preferably in a quantitative or technical field such as physics, mathematics, or computer science.

  • Advanced degrees (Master’s or Ph.D.) in related domains are preferred, especially for candidates who wish to stand out in the selection process.

  • The candidate should be well-versed in the complete machine learning development lifecycle.

  • Familiarity with both structured and unstructured data, as well as a solid grasp of Natural Language Processing (NLP), Graph Theory, and Generative AI technologies, is highly valued.

  • The role also demands strong data engineering skills to overcome friction points in real-world ML applications.

  • The ideal candidate will possess intellectual integrity, practical problem-solving skills, and adaptability to ambiguity and high-pressure scenarios.


Additional Info:

  • You'll be expected to work independently and also contribute to cross-functional teams to develop innovative ML-based business solutions.

  • The position may require balancing multiple projects simultaneously while meeting deadlines and maintaining high-quality outputs.

  • Your communication skills should be strong enough to present findings clearly to both technical teams and business stakeholders.

  • The culture supports knowledge sharing, mutual learning, and the constant pursuit of improvement through peer review and feedback.

  • Staying updated with the latest in academic and industrial data science trends will be an integral part of your growth in this role.

  • The job requires hands-on experience with model development, deployment, monitoring, and retraining pipelines.


Key Responsibilities

Machine Learning Development and Implementation:

  • Translate internal and client business requirements into machine learning use cases.

  • Select the right algorithms and models to apply for different types of problems.

  • Run full-cycle machine learning projects - from data preparation to production deployment.

  • Evaluate models using statistical techniques and deploy models for inference.

  • Monitor deployed models and manage model retraining cycles as needed.

Business and Technical Communication:

  • Clearly explain technical results and model behavior to non-technical business stakeholders.

  • Present detailed analysis and insights to data teams, management, and customers.

  • Use storytelling with data to support business cases and influence decisions.

  • Defend the model choices, underlying assumptions, and expected outcomes in both layman’s and technical terms.

Collaboration and Teamwork:

  • Work collaboratively with other business units and cross-functional teams.

  • Participate in idea generation sessions and brainstorming meetings.

  • Support other team members and openly share knowledge and learnings.

  • Seek continuous feedback and contribute to building a stronger data science community within the organization.

Self-Management and Delivery:

  • Manage multiple data science projects independently.

  • Meet project deadlines while delivering high-quality analytical solutions.

  • Be ready to adapt and pivot when needed to meet business requirements.

  • Take ownership and demonstrate accountability for end-to-end solutions.

Continuous Learning and Innovation:

  • Keep up-to-date with the latest research, tools, and industry trends in data science.

  • Apply innovative techniques from academia and industry to improve model performance.

  • Use intellectual curiosity to propose new project ideas or enhancements to existing solutions.

  • Attend workshops, webinars, and courses to enhance your skillset.


Desired Technical Skills

  • Python, R, or similar programming languages used in data science

  • Strong hands-on experience with SQL for data extraction and transformation

  • Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch

  • Understanding of statistical analysis, experimental design, and optimization techniques

  • Familiarity with cloud platforms and DevOps tools for model deployment

  • Experience with version control (e.g., Git), containerization (e.g., Docker), and CI/CD pipelines

  • Ability to work with structured, semi-structured, and unstructured data sources


Soft Skills and Competencies

  • Ability to operate in ambiguous, high-pressure situations and still deliver results

  • Strong analytical mindset paired with creative problem-solving skills

  • Excellent verbal and written communication abilities

  • Intellectual honesty - able to admit limitations of your work and seek improvement

  • Natural curiosity and a desire to keep learning and growing

  • Adaptability to change and resilience in dynamic work settings


Benefits Overview

  • Generous PTO policy that increases with tenure

  • Up to 16 weeks of 100% paid parental leave after one year

  • Sick leave for both self and family care

  • Access to education assistance and continuous training platforms

  • Participation in the Do Good Program - includes paid volunteer days and donation matching

  • Comprehensive 401(k) retirement savings plan with employer matching

  • Health benefits including medical, dental, and vision insurance for employees and dependents

  • Discounted membership plans for wellness programs (e.g., Wellhub)


Workplace Culture and Commitment

  • Dun & Bradstreet strongly supports equal opportunity employment and maintains a diverse and inclusive workplace

  • The company participates in E-Verify and complies with all legal regulations regarding discrimination and applicant rights

  • Reasonable accommodations are provided for individuals with disabilities

  • The organization encourages employee involvement in social good, community engagement, and environmental sustainability

  • Team members are given the flexibility to grow across teams and explore various career pathways internally


Please click here to apply.


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