June 22, 2026For 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. If you received an email purporting to be from Leidos that asks for payment-related information or any other personal information (e.g., about you or your previous employer), and you are concerned about its legitimacy, please make us aware immediately by emailing us at LeidosCareersFraud@leidos.com.
April 9, 2026For 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. If you received an email purporting to be from Leidos that asks for payment-related information or any other personal information (e.g., about you or your previous employer), and you are concerned about its legitimacy, please make us aware immediately by emailing us at LeidosCareersFraud@leidos.com.
June 22, 2026For 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. If you received an email purporting to be from Leidos that asks for payment-related information or any other personal information (e.g., about you or your previous employer), and you are concerned about its legitimacy, please make us aware immediately by emailing us at LeidosCareersFraud@leidos.com.
Additional or preferred qualifications:** + Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) + OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) + OR equivalent experience. **Qualifications** + Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) + OR Master's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 7+ years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) + OR Bachelor's Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10+ years data science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results) + OR equivalent experience.
Qualifications Required: + Master's or PhD degree in a relevant STEM field (Data Science, Computer Science, Engineering, Mathematics, Physics, etc.) + 3+ years of experience in AI/ML algorithm development using core data science languages and frameworks (Python, PyTorch, etc.) and data analysis (NLP, time-series analysis, computer vision) + 3+ years of experience and a proven track record applying traditional ML and deep learning techniques (CNNs, RNNs, GANs) across real-world projects, including model tuning and performance validation in production environments + 3+ years of experience deploying and optimizing ML models using tools like Kubernetes, Docker, TensorRT/Trion, RAPIDs, Kubeflow, and MLflow + 3+ years of experience in leveraging cloud environments (AWS, Azure, or GCP) to deploy AI/ML workloads + Live within commuting distance to one of Deloitte's consulting offices + Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve + Limited immigration sponsorship may be available Preferred: + 2+ years of experience working in a client-facing, consulting environment + 2+ years of experience leading project/client engagement teams in the execution of complex AI data science solutions + 1+ year of experience with LLM/GenAI use cases and developing RAG solutions, tools, and services (i.e., LangChain, LangGraph, MCP, etc.) + 1+ year of experience with AWS Sagemaker or AWS ML Studio The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. Key responsibilities include: + Guide clients with high autonomy in AI strategy and development, including understanding organizational needs, performing exploratory data analysis, building and validating models, and deploying models into production + Lead client initiatives to deliver AI/ML solutions, including providing thought leadership, long-term maintenance, and AI strategy objectives + Research and implement novel machine learning approaches, including advancing state-of-the-art training, solution design, network design, and hardware optimization + Validate AI models and algorithm via code reviews, unit, and integration tests + Support prioritization of project performance and model development and ensure AI solutions are delivered to maximize business impact and new initiatives + Collaborate with data engineers, data scientists, project managers, and business teams to make sure delivery and presentations align with business objectives A successful candidate would possess these skills: + Ability to work independently and collaborate as part of a team + Effective written and verbal communication skills + Meticulous attention to detail and quality of work product + Ability to build and sustain professional relationships + Ability to lead projects or workstreams + Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment + Strong interpersonal skills and professional demeanor + Ability to meet deadlines + Ability to provide clear guidance to others The TeamOur Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.
D. in a relevant STEM field (Data Science, Computer Science, Engineering, Physics, Mathematics, etc.) + 2+ years of experience in AI/ML algorithm development using core data science languages and frameworks (Python, PyTorch, etc.) and data analysis (NLP, time-series analysis, computer vision) + 2+ years of experience and a proven track record applying traditional ML and deep learning techniques (CNNs, RNNs, GANs) across real-world projects, including model tuning and performance validation in production environments + 2+ years of experience deploying and optimizing ML models using tools like Kubernetes, Docker, TensorRT/Triton, RAPIDs, Kubeflow, and MLflow + 2+ years of experience in leveraging cloud environments (AWS, Azure, or GCP) to deploy AI/ML workloads + Live within commuting distance to one of Deloitte's consulting offices + Ability to travel 10%, on average, based on the work you do and the clients and industries/sectors you serve + Limited immigration sponsorship may be available Preferred: + 2+ years of experience working in a client-facing, consulting environment + 1+ years of experience leading project/client engagement teams in the execution of complex AI data science solutions + 1+ year of experience with LLM/GenAI use cases and developing RAG solutions, agent-based tools and services, and GenAI frameworks (i.e., LangChain, LangGraph, MCP, etc.) + 1+ year of experience with AWS Sagemaker or AWS ML Studio The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. Key responsibilities include: + Guide clients with high autonomy in AI strategy and development, including understanding organizational needs, performing exploratory data analysis, building and validating models, and deploying models into production + Participate in client initiatives to deliver AI/ML solutions, including providing thought leadership, long-term maintenance, and AI strategy objectives + Research and implement novel machine learning approaches, including advancing state-of-the-art training, solution design, network design, and hardware optimization + Validate AI models and algorithm via code reviews, unit, and integration tests + Support prioritization of project performance and model development and ensure AI solutions are delivered to maximize business impact and new initiatives + Collaborate with data engineers, data scientists, project managers, and business teams to make sure delivery and presentations align with business objectives A successful candidate would possess these skills: + Ability to work independently and collaborate as part of a team + Effective written and verbal communication skills + Meticulous attention to detail and quality of work product + Ability to build and sustain professional relationships + Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment + Strong interpersonal skills and professional demeanor + Ability to meet deadlines + Ability to provide clear guidance to others The Team Our Strategy offering architects bold strategies to achieve business and mission goals, enabling growth, competitive advantage, technology modernization, and continuous digital and AI transformation.