Dataverse, Data Science Lead

🔥 0 minutes ago

🏛️ District of Columbia, Washington – Remote

🏛️ District of Columbia – Remote ☕ Washington – Remote

💵 $111.2k - $180.3k / year

⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

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LMI

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 1961

📦 Logistics

🏥 Healthcare

🎖️ Defense

Logistics • Healthcare • Defense

LMI is a forward-thinking company that focuses on reimagining the path from insight to outcome through innovative solutions in various sectors, including applied AI and digital health. They provide advanced analytics, engineering support, and performance optimization across defense, health, and civilian markets, with a strong commitment to enhancing mission effectiveness for government clients. With a focus on collaboration and research, LMI aims to drive positive change through its diverse capabilities and partnerships.

📋 Description

• Lead analytical strategy for complex operational, workflow, technology, and programmatic questions • Serve as subject-matter expert for Microsoft Dataverse data structures, management practices, analytical use cases, and integrations • Assess data readiness, quality, completeness, sensitivity, lineage, authoritative sources, access, and fitness for intended measures • Design and maintain reporting-ready Dataverse data models, tables, relationships, transformations, validation rules, business logic, and analytical pipelines • Develop, review, and apply statistical models, machine-learning methods, exploratory analyses, predictive analytics, and AI/LLM evaluations • Perform hands-on analysis using Python, SQL, Dataverse queries, and related tools • Partner with program, operational, technical, evaluation, and data-governance stakeholders on analytical foundations and evidence limitations • Translate complex findings into concise, actionable products for technical and nontechnical decision-makers • Lead feature definition, model selection, validation, error analysis, sensitivity testing, bias and fairness assessments, and interpretation • Establish analytical standards and governance for reproducibility, peer review, validation, documentation, version control, and data-quality checks • Create reusable notebooks, SQL scripts, code patterns, templates, Dataverse standards, data dictionaries, and quality checks • Coach analysts, data scientists, and technical teams • Coordinate with data engineering, platform, application-development, and Power Platform resources on pipelines, integrations, handoff, monitoring, security, and maintainability • Lead technical reviews of analytical plans, data models, methods, and results • Partner with data owners and governance stakeholders to improve definitions, provenance, access, quality, retention, and responsible-use controls • Support dashboards, reports, and self-service analytical products • Remain current on data governance, privacy, security, analytical methodologies, Dataverse capabilities, and responsible AI

🎯 Requirements

• U.S. citizenship required • Ability to obtain a CBP Background Investigation (BI) required; active CBP BI preferred • Master’s degree or higher in statistics, data science, operations research, public health, computer science, engineering, mathematics, or another related quantitative discipline • At least 9 years of progressive experience in applied data science, advanced analytics, statistical analysis, data engineering, or related analytical roles • Experience in federal health, healthcare, regulated-data environments, enterprise modernization, or similarly complex mission-driven organizations • Experience leading complex analytical efforts from problem definition through data assessment, analysis, validation, interpretation, and communication • Strong hands-on experience with Python and SQL • Experience designing and assessing data models, data pipelines, data-quality controls, validation logic, data lineage, authoritative data sources, and reporting-ready datasets • Experience with advanced analytical methods including predictive modeling, time-series analysis, causal inference, natural-language processing, machine learning, generative AI, or large language model evaluation • Experience with modern data, analytics, and visualization platforms such as Microsoft Dataverse, Databricks, Snowflake, Power BI, Azure, AWS, Google Cloud Platform, or comparable technologies • Ability to communicate analytical methods, results, uncertainty, assumptions, bias, data-quality concerns, and limitations clearly • Experience establishing or applying analytical standards for reproducibility, peer review, documentation, version control, quality assurance, validation, and responsible use of data and AI • Technical leadership experience, including mentoring analysts or data scientists, leading peer reviews, developing reusable analytical standards or assets, or managing complex analytical workstreams • 20% travel, potentially involving remote and rugged areas • Preferred: doctoral degree; healthcare, federal health, clinical analytics, public health, or operations research experience; analytics or machine-learning operationalization; NLP, generative AI, or LLM solution evaluation; Dataverse and Microsoft Power Platform experience; advanced technical certifications; recognized technical leadership evidence