Data Scientist, AI Engineer (R-18525)

10 Minutes ago • All levels

Research Development

Job Description

Dun & Bradstreet is seeking a Data Scientist, AI Engineer to drive innovation using Machine Learning and Generative AI. This role involves transforming complex business problems into scalable GenAI solutions, collaborating across teams, and working on cutting-edge projects. Key responsibilities include leveraging Large Language Models for insights, applying AI engineering best practices, and managing the full ML development cycle from data collection to deployment. The ideal candidate will have an advanced degree in a quantitative field and strong proficiency in Python, SQL, LLMs, and Big Data platforms.

Must Have:

Leverage Large Language Models (LLMs) to extract actionable insights from unstructured text data, designing and implementing robust GenAI pipelines.
Stay current with the rapidly evolving GenAI landscape, continuously exploring and applying state-of-the-art techniques, tools, and research.
Apply AI engineering best practices to design, build, and deploy intelligent agents and modular GenAI systems, integrating tools such as LangChain and vector databases.
Design and implement full ML development cycle: data collection, transformation, experimentation, model training, model finetuning, deployment, and monitoring.
Translate internal and client business cases into machine learning and GenAI frameworks.
Advanced degree (PhD or Master’s) in Physics, Mathematics, Computer Science, or a related quantitative field.
Proficiency in Python and SQL, with hands-on experience in core machine learning and data science frameworks such as Hugging Face, Pandas, NumPy, Scikit-learn, and PyTorch.
Hands-on experience with large language models (LLMs); parameter efficient finetuning (PEFT), Chain-of-Thought (CoT) prompting, RAG, LLM-as-a-judge.
Hands-on experience with Agentic AI development and orchestration libraries- LangChain and LangGraph.
Strong background in supervised/unsupervised Machine Learning frameworks, NLP, unstructured data analysis, and GenAI/LLMs.
Proficient in working with Big Data platforms (e.g., Databricks, Snowflake), with a strong foundation in data engineering.

Perks:

Generous paid time off in your first year, increasing with tenure.
Up to 16 weeks 100% paid parental leave after one year of employment.
Paid sick time to care for yourself or family members.
Education assistance and extensive training resources.
Do Good Program: Paid volunteer days & donation matching.
Competitive 401k with company matching.
Health & wellness benefits, including discounted Wellhub membership rates.
Medical, dental & vision insurance for you, spouse/partner & dependents.

Add these skills to join the top 1% applicants for this job

communication

data-analytics

unity

game-texts

data-science

numpy

scikit-learn

pytorch

pandas

python

sql

machine-learning

Why We Work at Dun & Bradstreet

Dun & Bradstreet unlocks the power of data through analytics, creating a better tomorrow. Each day, we are finding new ways to strengthen our award-winning culture and accelerate creativity, innovation and growth. Our 6,000+ global team members are passionate about what we do. We are dedicated to helping clients turn uncertainty into confidence, risk into opportunity and potential into prosperity. Bold and diverse thinkers are always welcome. Come join us! Learn more at dnb.com/careers

We are hiring a Data Scientist, AI Engineer to join our team and help drive innovation through Machine Learning and Generative AI.

The Data Scientist, AI Engineer will work on cutting-edge projects, transforming complex business problems into scalable GenAI solutions, and collaborating across teams to deliver results.

Responsibilities:

Leverage Large Language Models (LLMs) to extract actionable insights from unstructured text data, designing and implementing robust GenAI pipelines tailored to diverse business needs.
Stay current with the rapidly evolving GenAI landscape, continuously exploring and applying state-of-the-art techniques, tools, and research to enhance model performance and innovation.
Apply AI engineering best practices to design, build, and deploy intelligent agents and modular GenAI systems, integrating tools such as LangChain and vector databases to enable dynamic reasoning and autonomous task execution.
Design and implement full ML development cycle: data collection, transformation, experimentation, model training, model finetuning, deployment, and monitoring.
Translate internal and client business cases into machine learning and GenAI frameworks.
Balance independent work with collaborative team efforts.

Required Qualifications:

Advanced degree (PhD or Master’s) in Physics, Mathematics, Computer Science, or a related quantitative field.
Proficiency in Python and SQL, with hands-on experience in core machine learning and data science frameworks such as Hugging Face, Pandas, NumPy, Scikit-learn, and PyTorch.
Hands-on experience with large language models (LLMs); parameter efficient finetuning (PEFT), Chain-of-Thought (CoT) prompting, RAG, LLM-as-a-judge.
Hands-on experience with Agentic AI development and orchestration libraries- LangChain and LangGraph .
Strong background in supervised/unsupervised Machine Learning frameworks, NLP, unstructured data analysis, and GenAI/LLMs.
Proficient in working with Big Data platforms (e.g., Databricks, Snowflake), with a strong foundation in data engineering and the ability to independently troubleshoot and resolve data-related issues.
Excellent communication skills with the ability to explain complex concepts clearly.
Demonstrate intellectual honesty, curiosity, and practical problem-solving.

Benefits We Offer