Data Scientist II - WFH

About the Company
The Cole Group specializes in placing CROs, CMOs, and go-to-market leaders at high-growth software companies, including organizations across AI and B2B technology. The company uses its proprietary platform, Rolodex, to manage data generated through candidate searches, client interactions, and hiring outcomes. It is developing Rolodex into a learning system that turns this information into actionable insights for consultants.
About the Role
The Cole Group is seeking a Senior Data Scientist to lead the modeling and intelligence capabilities behind Rolodex. This is a hands-on role focused on transforming data from candidate searches, consultant activities, client interactions, notes, transcripts, references, and outcomes into useful signals that improve decision-making.
You will build, deploy, evaluate, and continuously improve models in collaboration with the engineering team. Your work will help Rolodex become more effective at identifying and ranking candidates, finding similarities between candidates and companies, extracting insights from unstructured text, and explaining the reasoning behind its recommendations.
The ideal candidate has experience building production machine learning systems, working with large language models (LLMs), and delivering explainable solutions that business users can understand and trust.
Key Responsibilities
•Develop and improve models that adapt as consultants interact with Rolodex and searches progress.
•Build candidate scoring and ranking systems that become more effective as new search activity and outcomes generate additional data.
•Develop systems for processing unstructured text, including call transcripts, consultant notes, and references.
•Apply prompt engineering, named entity recognition, and information extraction techniques to convert unstructured information into structured features.
•Design and build models that identify similar candidates, companies, and jobs using proprietary data.
•Create feedback loops that incorporate completed search outcomes into models to support continuous learning and improvement.
•Deploy models into production in collaboration with the engineering team.
•Evaluate model performance, identify areas for improvement, and refine models based on real-world results.
•Develop explainable models that show why candidates, companies, or jobs are surfaced, ranked, or recommended.
•Make the evidence, contributing signals, and levels of confidence or uncertainty behind model outputs accessible to consultants and clients.
•Work directly with non-technical business users to define unclear problems, understand their needs, and deliver solutions they adopt.
Required Qualifications
•Experience building and deploying a production scoring or ranking system used by people to make real-world decisions.
•Experience taking machine learning models through an engineering release process and into production.
•Practical experience using large language models (LLMs) to extract structured information or features from unstructured text, including transcripts, notes, or free-form content.
•Ability to evaluate model performance using appropriate benchmarks and explain how the results affected downstream processes.
•Experience building explainable models whose outputs need to be understood and trusted by end users.
•Ability to communicate model reasoning, supporting evidence, and uncertainty in a clear and useful way.
•Experience working directly with non-technical stakeholders to define business problems and deliver solutions that are adopted.
•Strong Python and SQL skills.
•Experience working with LLM APIs.
Technical Skills & Tools
•Python and SQL for data processing and model development.
•LLM APIs and prompt engineering.
•Agent or LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, DSPy, or comparable tools.
•Retrieval systems and embedding tools.
•Machine learning model deployment, evaluation, and continuous improvement.
Employment Details
•Job Title: Senior Data Scientist
•Company: The Cole Group
•Work Arrangement: Fully remote
•Location: United States
•Employment Type: Not specified
•Salary and Benefits: Not specified

Work arrangement
Yes