Data Scientist

Job not on LinkedIn

🔥 10 minutes ago

🦀 Maryland – Remote

🦀 Maryland – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

📊 Data Scientist

👻 Ghost score 15%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Black Canyon Group Inc.

WebsiteLinkedInAll Job Openings

1 - 10 employees

💼 Consulting

📣 Marketing

📚 Education

Consulting • Marketing • Education

Black Canyon Group Inc. is an E-Learning provider that specializes in equipping B2B executives with the skills and strategies needed to compete, win, grow, and thrive in their markets. Focused on small-to-medium-sized and privately-held companies, the group emphasizes B2B marketing, professional development, and strategic business practices. They are known for their creation of the NanoMarketing Method ®, a precise system aimed at enhancing business development for organizations whose customers are other businesses and not individual consumers.

📋 Description

• Develop analytical and machine-learning approaches supporting permitting and natural-resource use cases • Build and maintain labeled datasets, evaluation corpora, and benchmark datasets for AI-enabled services • Define quantitative evaluation methodologies for classification, extraction, retrieval, summarization, entity matching, and other AI/NLP capabilities • Evaluate LLM and agentic workflows, including output quality, retrieval performance, task completion, failure modes, and reliability • Analyze public-comment datasets and develop reusable features and evaluation datasets for comment-processing services • Apply NLP and machine-learning techniques to structured and unstructured data • Evaluate embedding models, semantic retrieval strategies, document-ranking techniques, and AI-generated outputs • Develop statistical approaches for detecting anomalies, reconciliation issues, missing data, and inconsistent records • Partner with Content Pipeline Engineers to measure OCR, extraction, and document-retrieval performance • Partner with Data Engineers to ensure analytical datasets and evaluation pipelines are reproducible and production-ready • Support entity matching and harmonization across data originating in multiple source systems • Design experiments and validation approaches with clearly defined success metrics • Contribute to certified analytical data products, metrics, and governed datasets • Develop reproducible Python analyses, models, evaluation pipelines, and technical documentation • Communicate model performance, limitations, uncertainty, and failure modes to technical and non-technical stakeholders

🎯 Requirements

• Bachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Engineering, or a related quantitative discipline • 5+ years of relevant data science, applied machine learning, or quantitative analytics experience • Strong Python and SQL skills • Experience with statistical analysis, machine learning, NLP, and unstructured text data • Experience designing labeled datasets, benchmark datasets, and train/test evaluation frameworks • Experience evaluating LLM, RAG, or agentic AI solutions, including retrieval quality, output accuracy, and failure modes • Strong understanding of model-evaluation techniques, including precision, recall, F1, ranking metrics, confusion matrices, and related measures • Experience with embeddings, semantic retrieval, or vector-based search • Experience developing reproducible analytical and evaluation workflows • Ability to distinguish data-quality issues from model-performance issues • Strong ability to communicate analytical results, limitations, and uncertainty • Bonus: Experience with agent evaluation frameworks or LLM observability tools • Bonus: Experience with agentic frameworks such as LangChain, LangGraph, or similar orchestration frameworks • Bonus: Experience with OpenSearch, vector databases, or enterprise search platforms • Bonus: Experience with document AI or OCR pipelines • Bonus: Experience with geospatial analysis • Bonus: Experience developing entity-resolution, record-linkage, or data-quality models • Bonus: Experience working in the U.S. Federal Government space • Bonus: Experience with permitting, regulatory, environmental, energy, or natural-resource datasets

🏖️ Benefits

• Medical coverage • Dental coverage • Vision coverage • 401k plan with employer contribution • Paid holidays • Vacation • Tuition reimbursement

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