Title: Senior Data Scientist Rockville, MD Alexandria, VA Job Description: Are you ready to thrive? Through training, teamwork, and exposure to challenging technical work, let Leidos show how to accelerate your career path. Join Leidos' all-star team supporting the Defense Intelligence Agency's Enterprise Digital Modernization Accelerator initiative. This program is at the forefront of deploying enterprise-scale AI, data, and mission platform capabilities across cloud, edge, and classified environments. We are looking for creative, driven, and mission-focused professionals ready to take their career to the next level. As a Senior Data Scientist, you will: - Lead the design, development, and deployment of advanced analytics and AI/ML solutions for mission-critical applications. - Collaborate with multidisciplinary teams of analysts, engineers, and developers to solve complex challenges and deliver innovative, production-ready algorithms and platforms. - Apply cutting-edge techniques in statistical analysis, predictive analytics, entity resolution, graph analytics, explainable AI, and operational analytics. - Work with diverse data types (structured, unstructured, open source, digital media) and leverage modern tools such as Python, PyTorch, Scikit-learn, LLM frameworks, and geospatial analytics platforms. - Contribute to the integration of AI, DevSecOps, data engineering, platform engineering, cybersecurity, and observability in a fast-paced, engineering-centric environment. - Enjoy flexible work arrangements, including remote and on-site work in the National Capital Region (Rockville, MD and/or Alexandria, VA). What You Bring: - Bachelor's, Master's, or equivalent graduate degree in a quantitative or analytical field (Computer Science, Mathematics, Statistics, Engineering, Physics, Computational Social Science, etc.). Relevant experience may be substituted for a degree. - 12+ years of experience in data science, analytics, or quantitative intelligence analysis, developing analytics and AI/ML solutions (10+ years with a Master's). - Active Top Secret clearance and eligibility for TS/SCI with Polygraph. - Proficiency in Python and at least one other scripting language. - Demonstrated experience collaborating with hybrid teams to research, build, and deploy complex, user-friendly analytical platforms. - Track record of creative problem solving, active learning, and mission-focused outcomes. - Familiarity with version control tools (git, svn, JIRA) and deployment technologies (Docker, Kubernetes, OpenShift). Preferred Qualifications: - Experience supporting military or intelligence community customers. - Expertise with knowledge graphs (neo4j, graph ML), predictive algorithms, image classifiers, object detectors, information retrieval, SQL, Elastic Stack. - Experience deploying data science applications (e.g., Streamlit) and working with distributed systems (Hadoop, Ray, Spark). - Familiarity with Azure/C2S, hardware platforms (CPUs, GPUs, FPGAs), and advanced analytical methodologies (social network analysis, supply chain analysis, NLP, classification algorithms, image processing). - Experience with Large Language Models (LLMs), Multimodal LLMs, Langchain, vLLM, llama.cpp. If you're looking for comfort, keep scrolling. At Leidos, we outthink, outbuild, and outpace the status quo - because the mission demands it. We're not hiring followers. We're recruiting the ones who disrupt, provoke, and refuse to fail. Step 10 is ancient history. We're already at step 30 - and moving faster than anyone else dares. For U.S. Positions: While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above. Pay Range: Pay Range $131,300.00 - $237,350.00 The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.

• Develop price elasticity curves to forecast the impact of rating changes on policyholder retention and conversion, and assess their impact on customer lifetime value • Forecast policyholder retention and conversion for the portfolio based on pricing, operational changes, and business initiatives • Improve the risk segmentation sophistication of our rating plans by developing GLM-based rating factors (in R or Python) and applying advanced predictive modeling techniques • Build and maintain tools to monitor the performance of our existing rating plans and rate level over time, including loss ratio, conversion rate, churn, and lifetime value • Write advanced SQL procedures to pull from large, line item level veterinary bill databases • Estimate the impact of coverage and product changes on pricing • Analyze product design proposals to determine pricing viability, impact on enterprise risk, competitive positioning, and customer value • Stay highly informed on competitor filings to understand how our products and pricing stand relative to the market • Support rate filing and rate indication work, including the development of filings and responses to regulatory objections • Operate seamlessly with product, underwriting, marketing, BI, and IT teams, and communicate complex actuarial concepts to a non-actuarial audience • Propose creative ways to price innovative coverage concepts and ideas

Role Description A área de Engenharia Centrada em IA é dinâmica e empolgante, fazendo parte do Escritório do CTO (OCTO) da Dell. Conduzimos pesquisas e engenharia voltadas para o futuro da Dell Technologies em um ambiente de alta visibilidade e colaboração intensa. Nossa equipe é especializada no desenvolvimento de soluções avançadas de IA que capacitam empresas a inovar, se comunicar e otimizar operações de maneiras nunca antes possíveis. Somos compostos por pessoas apaixonadas e dedicadas a ultrapassar os limites da tecnologia de IA. Como Cientista de Dados você será responsável por: - Contribuir com a estratégia de negócios e influenciar a tomada de decisões com base em informações obtidas por meio de análises aprofundadas. - Produzir recomendações acionáveis e envolventes ao interpretar insights de conjuntos de dados complexos. - Projetar processos para consolidar e examinar dados não estruturados, gerando insights relevantes. - Colaborar com líderes de negócios, engenheiros e especialistas da indústria para construir modelos preditivos, algoritmos e motores de probabilidade. Qualifications - Experiência em análise de dados e modelagem estatística. - Conhecimento em linguagens de programação como Python ou R. - Habilidade em trabalhar com grandes conjuntos de dados. - Capacidade de comunicar insights de forma clara e eficaz. Requirements - Formação em Ciência da Computação, Estatística, Matemática ou áreas relacionadas. - Experiência prévia em um papel similar. - Familiaridade com ferramentas de visualização de dados. Benefits - Trabalho remoto. - Oportunidades de crescimento e desenvolvimento profissional. - Ambiente de trabalho inclusivo e diversificado.

• Design, develop, and deploy scalable data science, machine learning, and AI solutions that drive business value • Build production-ready ML pipelines, from feature engineering and model development through deployment and monitoring • Develop AI-powered applications using modern frameworks such as Streamlit and integrate Large Language Models (LLMs) into business workflows • Design and maintain Retrieval-Augmented Generation (RAG) solutions, knowledge bases, and AI agents using structured and unstructured enterprise data • Perform quantitative and qualitative analyses to identify trends, generate insights, and support strategic decision-making • Partner with business stakeholders to translate complex business challenges into scalable AI and analytics solutions • Collaborate with data engineers, software engineers, analysts, and product teams on cross-functional initiatives • Improve existing data science processes, identify automation opportunities, and promote engineering best practices • Contribute to technical documentation, knowledge sharing, and continuous improvement initiatives