Position:
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Data Scientist
Company:
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Dun & Bradstreet
Location:
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Florham Park, New Jersey, United States
Job type:
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Full-time
Job mode:
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On-site
Job requisition id:
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R-17845
Years of experience:
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Not explicitly required, but suited for entry-level to early-career professionals
Company Description
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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.
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The company has a history of over 180 years in delivering reliable data-driven insights to businesses worldwide.
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With over 6,000 professionals globally, D&B’s team is passionate about innovation and focused on turning potential into prosperity.
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The culture is award-winning, grounded in creativity, collaboration, and growth, welcoming individuals with bold, diverse thinking.
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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:
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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.
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You will work on transforming complex business cases, both internal and from clients, into well-structured ML-based solutions.
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The job involves identifying business needs independently, running multiple ML projects in parallel, and explaining results to both technical and non-technical stakeholders.
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Collaboration across teams is key, but self-driven problem-solving and time management are equally important in the fast-paced environment.
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There is a strong emphasis on continuous learning, sharing of knowledge, and applying the latest academic and industry research.
Qualifications:
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A bachelor’s degree is required, preferably in a quantitative or technical field such as physics, mathematics, or computer science.
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Advanced degrees (Master’s or Ph.D.) in related domains are preferred, especially for candidates who wish to stand out in the selection process.
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The candidate should be well-versed in the complete machine learning development lifecycle.
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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.
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The role also demands strong data engineering skills to overcome friction points in real-world ML applications.
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The ideal candidate will possess intellectual integrity, practical problem-solving skills, and adaptability to ambiguity and high-pressure scenarios.
Additional Info:
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You'll be expected to work independently and also contribute to cross-functional teams to develop innovative ML-based business solutions.
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The position may require balancing multiple projects simultaneously while meeting deadlines and maintaining high-quality outputs.
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Your communication skills should be strong enough to present findings clearly to both technical teams and business stakeholders.
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The culture supports knowledge sharing, mutual learning, and the constant pursuit of improvement through peer review and feedback.
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Staying updated with the latest in academic and industrial data science trends will be an integral part of your growth in this role.
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The job requires hands-on experience with model development, deployment, monitoring, and retraining pipelines.
Key Responsibilities
Machine Learning Development and Implementation:
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Translate internal and client business requirements into machine learning use cases.
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Select the right algorithms and models to apply for different types of problems.
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Run full-cycle machine learning projects - from data preparation to production deployment.
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Evaluate models using statistical techniques and deploy models for inference.
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Monitor deployed models and manage model retraining cycles as needed.
Business and Technical Communication:
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Clearly explain technical results and model behavior to non-technical business stakeholders.
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Present detailed analysis and insights to data teams, management, and customers.
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Use storytelling with data to support business cases and influence decisions.
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Defend the model choices, underlying assumptions, and expected outcomes in both layman’s and technical terms.
Collaboration and Teamwork:
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Work collaboratively with other business units and cross-functional teams.
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Participate in idea generation sessions and brainstorming meetings.
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Support other team members and openly share knowledge and learnings.
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Seek continuous feedback and contribute to building a stronger data science community within the organization.
Self-Management and Delivery:
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Manage multiple data science projects independently.
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Meet project deadlines while delivering high-quality analytical solutions.
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Be ready to adapt and pivot when needed to meet business requirements.
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Take ownership and demonstrate accountability for end-to-end solutions.
Continuous Learning and Innovation:
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Keep up-to-date with the latest research, tools, and industry trends in data science.
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Apply innovative techniques from academia and industry to improve model performance.
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Use intellectual curiosity to propose new project ideas or enhancements to existing solutions.
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Attend workshops, webinars, and courses to enhance your skillset.
Desired Technical Skills
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Python, R, or similar programming languages used in data science
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Strong hands-on experience with SQL for data extraction and transformation
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Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch
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Understanding of statistical analysis, experimental design, and optimization techniques
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Familiarity with cloud platforms and DevOps tools for model deployment
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Experience with version control (e.g., Git), containerization (e.g., Docker), and CI/CD pipelines
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Ability to work with structured, semi-structured, and unstructured data sources
Soft Skills and Competencies
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Ability to operate in ambiguous, high-pressure situations and still deliver results
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Strong analytical mindset paired with creative problem-solving skills
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Excellent verbal and written communication abilities
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Intellectual honesty - able to admit limitations of your work and seek improvement
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Natural curiosity and a desire to keep learning and growing
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Adaptability to change and resilience in dynamic work settings
Benefits Overview
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Generous PTO policy that increases with tenure
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Up to 16 weeks of 100% paid parental leave after one year
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Sick leave for both self and family care
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Access to education assistance and continuous training platforms
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Participation in the Do Good Program - includes paid volunteer days and donation matching
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Comprehensive 401(k) retirement savings plan with employer matching
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Health benefits including medical, dental, and vision insurance for employees and dependents
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Discounted membership plans for wellness programs (e.g., Wellhub)
Workplace Culture and Commitment
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Dun & Bradstreet strongly supports equal opportunity employment and maintains a diverse and inclusive workplace
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The company participates in E-Verify and complies with all legal regulations regarding discrimination and applicant rights
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Reasonable accommodations are provided for individuals with disabilities
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The organization encourages employee involvement in social good, community engagement, and environmental sustainability
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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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