Statistical Engineering Jobs in Minnesota (NOW HIRING)

Are you passionate about building AI-enabled products that transform complex data into meaningful insights?

Do you enjoy combining software engineering, analytics, machine learning, and Generative AI to deliver innovative, customer-facing solutions?

About the Business

LexisNexis Risk Solutions is the essential partner in the assessment of risk. Within our Government vertical, our solutions assist government agencies and law enforcement to drive insights from complex data sets, improving operation efficiency, increasing program integrity, discovering, and recovering revenue, and making timely and informed decisions to enhance investigations. You can learn more about LexisNexis Risk athttps://risk.lexisnexis.com/government

About the Team

Opportunity for a curious and motivated Senior Data Scientist to make an impact on our fast-paced and cross-functional team of data scientists, software engineers, product managers, strategists, and domain experts. In this role, you will design, develop, and deploy advanced analytical capabilities that support AI-driven products serving government customers across civilian services, public health, and public safety.

About the Role

The ideal candidate combines strong software development skills with practical experience applying machine learning, statistical methods, and generative AI technologies to real-world problems. You will contribute to the development of scalable analytical services, intelligent decision-support capabilities, research initiatives, and production-grade AI features. If you enjoy building innovative solutions that bridge data science and software engineering, thrive in a collaborative environment, and are eager to solve complex challenges, we would like to hear from you.

Responsibilities

• Must be a US Citizen or Green Card holder.
• Independently scope, execute, and lead small-scale projects while contributing to larger, more complex initiatives.
• Design, develop, and maintain analytical applications, services, and reusable components that support AI-enabled products.
• Support the full analytical development lifecycle, including solution design, implementation, validation, deployment, and ongoing enhancement.
• Develop robust data pipelines and analytical workflows that transform large, complex datasets into actionable insights and product capabilities.
• Extract, clean, and design large and complex datasets to support analysis, experimentation, and product delivery.
• Build and operationalize statistical models, machine learning solutions, and intelligent decision-support capabilities.
• Contribute to the development of AI-powered product features through prompt engineering, retrieval strategies, workflow design, and integration of analytical capabilities.
• Write high-quality, maintainable code following software engineering best practices including testing, documentation, code reviews, and performance optimization.
• Communicate analytical findings and technical recommendations to both technical and non-technical stakeholders.
• Collaborate closely with software engineers, product managers, project managers, analysts, and architects to deliver customer-facing solutions.
• Support product development, research, prototyping, and innovation initiatives across the organization.

Required Qualifications

• Bachelor's degree in data science, Computer Science, Mathematics, Statistics, Engineering, or a related field, and 10+ years of relevant work experience; or a Master's degree in a related field and 5+ years of relevant work experience.
• Demonstrated experience applying data science, analytics, statistical, or engineering principles in a professional setting.
• Strong software development experience using Java and familiarity with modern development frameworks, design patterns, and object-oriented design principles.
• Proficient in Python, SQL, Pandas, NumPy, and related data science and analytical tooling.
• Experience building, integrating, and deploying analytical or AI-driven services within production environments.
• Demonstrates proficiency in machine learning, statistical modeling, data science frameworks, and generative AI technologies.
• Experience with Generative AI platforms and tools, including OpenAI, Microsoft Copilot, Claude, and related ecosystems.
• Familiarity with API development, service-oriented architectures, cloud-native applications, and software engineering best practices.
• Skilled in processing and manipulating large datasets, feature engineering, data preparation, and analytical workflow development.
• Experience designing analytical capabilities that combine software engineering, business logic, data science, and AI techniques to deliver reliable and explainable outcomes in production systems.
• Strong problem-solving skills with the ability to determine when statistical, machine learning, rules-based, or software-based approaches are most appropriate.
• Strong documentation, written communication, and verbal communication skills.
• Strong interpersonal skills with the ability to collaborate effectively across technical and non-technical teams.
• Organized with the ability to manage multiple concurrent priorities and projects.
• Self-starter with a strong desire to learn new technologies and approaches.
• Demonstrates leadership within small teams and project initiatives.
• Detail-oriented critical thinker with strong analytical and systems-thinking skills.

Learn more about the LexisNexis Risk team and how we work

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