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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - consultant - **Company:** SilverSearch, Inc. - **Location:** New York, United States - **Experience:** Experienced - **Salary:** $124,800.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Artificial Intelligence, Data Analysis, Encodings, Elasticsearch, Entity Relationship Models, Graph Database, JSON, Python (Programming Language), Search Algorithms, Machine Learning, Language Modeling, Natural Language Processing, Named Entity Recognition, NumPy, Open Source Technology, Model Validation, Pandas, Information Technology, Machine Learning Operations, GPT - **Published:** August 8, 2026 - **Apply:** https://www.dice.com/job-detail/02069ac4-ac69-4edc-a486-fa020c269dee ## About the Role * 3+ years of professional experience in Data Science or Applied Machine Learning. * Bachelor''s degree in Computer Science, Data Science, Machine Learning, or a related technical field. * Strong Python programming skills, including experience with NumPy, Pandas, and large-scale semi-structured (JSON) datasets. * Hands-on experience with core machine learning techniques including classification, clustering, regression, and ranking. * Experience applying NLP techniques such as: + Named Entity Recognition (NER) + Entity disambiguation + Semantic similarity + Embedding-based retrieval * Experience working with transformer-based models for extraction, classification, summarization, and text generation. * Experience building or improving hybrid search solutions, retrieval pipelines, query expansion, intent detection, and relevance tuning using Elasticsearch or OpenSearch. * Experience working with both language models and multimodal AI models. * Experience processing large-scale text and image datasets. * Familiarity with ML Engineering and MLOps practices, including deploying and maintaining production machine learning solutions. * Knowledge of experimentation methodologies including A/B testing, cohort analysis, session segmentation, and model evaluation metrics. * Strong analytical, problem-solving, and communication skills. * Ability to manage multiple concurrent projects in a fast-paced environment. * Experience working across the full machine learning development lifecycle., * Master''s degree in Computer Science, Data Science, Machine Learning, or a related discipline. * Experience with graph databases, knowledge graphs, or entity relationship modeling. * Experience designing scalable AI solutions for search, recommendation, or content intelligence platforms. * Experience working with large, evolving datasets in production environments. * Curiosity and interest in emerging AI technologies and practical applications of generative AI., * Hybrid work arrangement (multiple days onsite each week). * Must have Opensearch or Elasticsearch * Candidates must be authorized to work in the United States without current or future sponsorship. * $60/hr. W2 or $75/hr. IC (no C2C) ## Description Our client is seeking a Data Scientist to design and implement data science and applied machine learning solutions supporting new product development, intelligent search and discovery, content enrichment, and metadata generation. Working as part of a cross-functional team, you will evaluate commercial and open-source AI models, perform data analysis, and deliver production-ready solutions with measurable business impact. This role partners closely with engineering, product, and business stakeholders to develop end-to-end AI and machine learning solutions, improve data quality, and enhance search, retrieval, and content intelligence capabilities., * Evaluate, fine-tune, and maintain statistical and machine learning models deployed in production environments, measuring and communicating performance improvements. * Collaborate with cross-functional teams to design and optimize AI/ML solutions that support new product capabilities and improve internal workflows. * Research, evaluate, and recommend machine learning models and methodologies, presenting findings to both technical and non-technical stakeholders. * Analyze model quality and performance, identifying opportunities for improvement and translating findings into actionable recommendations. * Design and enhance data and machine learning pipelines, including multimodal embedding generation and knowledge extraction, with a focus on scalability, efficiency, and accuracy. * Develop user-focused search algorithms and retrieval solutions that maximize relevance and performance. * Stay current with advancements in NLP, machine learning, and generative AI, recommending new technologies and approaches where appropriate. * Support the complete machine learning lifecycle, including problem definition, experimentation, deployment, monitoring, and ongoing optimization. * Communicate analytical findings and technical concepts effectively to a wide range of audiences. ## Related Videos - [OLAP for AI Applications and why you should care](https://www.wearedevelopers.com/videos/100212-olap-for-ai-applications-and-why-you-should-care) - [Vectorize all the things! 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