{"id":3592631,"url":"https://alion.io/job/revolutional-lead-data-scientist","title":"Lead Data Scientist","company":{"id":4450998,"name":"Revolutional","domain":"revolutional.com","url":"https://alion.io/company/revolutional","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Greenhouse","truth_index":{"grade":"B","score":73,"open_postings":32,"ghost_share":0.531,"stale_share":0,"repost_share":0,"time_to_fill_p50_days":10,"computed_at":"2026-11-08T05:47:12Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["McLean, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":210000,"currency":"USD","period":"year","gross":null,"usd_annual":210000},"salary_estimate":null,"experience_years_min":15,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Anomaly Detection","optional":false},{"name":"CI/CD","optional":false},{"name":"Confluence","optional":false},{"name":"Databricks","optional":false},{"name":"Git","optional":false},{"name":"Jira","optional":false},{"name":"Machine Learning","optional":false},{"name":"NIST AI RMF","optional":false},{"name":"NLP","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Spark","optional":false},{"name":"TensorFlow","optional":false},{"name":"Time Series","optional":false},{"name":"AWS","optional":true},{"name":"Azure","optional":true}],"status":"live","first_seen_at":"2026-05-19T14:22:14Z","employer_posted_date":"2026-10-22","last_verified_at":"2026-11-08T07:32:23Z","board_verified":true,"closed_at":null,"days_open":172,"trust":{"level":"ghost","repost_count":0,"flags":["stale","company_stale"],"days_open":172},"description":"Revolutional delivers advanced technology solutions and mission support to federal agencies across civilian, health, and national security environments. We apply modern capabilities, including AI/ML, cloud, cybersecurity, and IT modernization to solve complex challenges, enable faster and more secure operations, and drive measurable mission outcomes.\nWe are redefining how federal technology gets built and delivered by operating with a product mindset, prioritizing speed, ownership, and execution over bureaucracy.\nLead Data Scientist\nLocation: Suitland, MD (Hybrid)\nTerms: Full-time\nClearance/Work Authorization: U.S. Citizenship with the ability to obtain and maintain a Public Trust is required\nSalary Range: $150-210k DOE\nTravel: %\nProject Description\nThis position supports Revolutional’s federal customer as part of an application transformation and modernization initiative.\nThis program is driving a large-scale transformation of systems into a data-centric, cloud-native ecosystem capable of supporting high-volume, near real-time data processing and advanced analytics. The work includes modernization of legacy applications, development of new cloud-native solutions, and implementation of DevSecOps and scaled Agile practices across the organization.\nThe core challenge: orchestrating complex, multi-contractor delivery while transforming both technology and operating models without disrupting mission-critical operations.\nPosition Description\nAs a Lead Data Scientist at Revolutional, you will define and drive enterprise data science and AI/ML strategy across a large-scale federal modernization program.\nYou will lead efforts spanning advanced analytics, machine learning, MLOps, AI governance, and operational analytics integration across complex enterprise systems. This role requires close collaboration with data engineering, architecture, application development, and operational teams to ensure AI/ML capabilities are production-ready, scalable, explainable, and integrated into enterprise workflows.\nYou will operate at both strategic and hands-on levels guiding technical direction, developing advanced models, and ensuring analytics solutions deliver measurable mission impact.\nResponsibilities\nProvide technical leadership across enterprise data science and AI/ML initiatives within a large-scale modernization program\nDesign, develop, validate, deploy, monitor, and scale machine learning and advanced analytics solutions in production environments\nLead implementation of MLOps practices supporting model lifecycle management, automation, observability, and continuous improvement\nApply advanced data science techniques including NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analysis\nDesign and support event-driven analytics and real-time/streaming ML pipelines\nCollaborate with data engineers, architects, application teams, and SMEs to integrate AI/ML capabilities into enterprise systems and operational workflows\nSupport system-of-systems (SoS) integrations across multiple systems, vendors, contractors, and interdependent platforms\nEstablish AI governance frameworks supporting fairness, bias mitigation, explainability, transparency, and compliance with standards such as the NIST AI Risk Management Framework\nDevelop reproducible analytics workflows, technical documentation, analysis plans, dashboards, and reporting deliverables\nSupport DataOps and Agile data science practices including iterative development, pipeline automation, CI/CD integration, and collaborative model delivery\nEnsure analytics solutions align with enterprise security, privacy, and compliance requirements\nDrive improvements in data quality, validation, accessibility, and operational analytics reliability\nPresent findings, recommendations, and technical approaches to executive leadership and stakeholders\nMentor data scientists and analytics teams while promoting best practices across the organization\nTechnical Environment\nCloud-native AI/ML and analytics environments (AWS, Azure)\nDistributed data platforms and enterprise analytics ecosystems\nPython, R, Spark, TensorFlow, PyTorch, Databricks, and related ML frameworks\nMLOps pipelines, model deployment platforms, and automation frameworks\nReal-time streaming and event-driven analytics systems\nDevSecOps pipelines and CI/CD automation practices\nDataOps and Agile/SAFe delivery environments\nAPIs, distributed integrations, and enterprise data platforms\nCollaboration and delivery tools (Git, Jira, Confluence)\nHigh-volume, near real-time processing environments\nWhat You Bring (Requirements)\nBaseline Requirements\nU.S. Citizenship with the ability to obtain a Public Trust\nPhD in Data Science, Computer Science, Statistics, Mathematics, or related field\n15+ years of experience in data science, AI/ML, advanced analytics, or enterprise modernization initiatives\nProven experience leading AI/ML and analytics efforts across large-scale, complex systems\nAbility to obtain and maintain a Public Trust clearance\nTechnical Capabilities\nDeep expertise in machine learning, statistical modeling, and advanced analytics techniques\nExperience implementing end-to-end MLOps pipelines including model training, validation, deployment, monitoring, and scaling\nExperience with NLP, LLMs, deep learning, reinforcement learning, anomaly detection, and time series analytics\nExperience designing and supporting real-time or streaming analytics architectures\nExperience integrating AI/ML solutions across system-of-systems (SoS) environments and distributed enterprise platforms\nExperience implementing AI governance frameworks addressing explainability, fairness, transparency, and bias mitigation\nExperience with large-scale distributed data environments and cloud-native analytics platforms\nExperience with DataOps, CI/CD integration, and Agile/SAFe delivery models\nStrong experience with Python, R, Spark, TensorFlow, PyTorch, Databricks, and related AI/ML technologies\nExperience developing dashboards, technical reports, analysis plans, and reproducible analytics workflows\nExperience collaborating across engineering, architecture, application, and operational teams at enterprise scale\nCore Strengths\nStrong ownership mindset with accountability for enterprise AI/ML outcomes\nAbility to translate complex analytical findings into actionable business and mission insights\nStrategic thinker capable of balancing innovation, governance, and operational realities\nEffective communication across technical, operational, and executive stakeholders\nStrong leadership and mentoring capabilities across data science and analytics teams\nAbility to operate in complex, fast-moving, multi-contractor delivery environments\nNice to Have (Differentiators)\nExperience supporting statistical and similarly large-scale federal modernization programs\nExperience implementing enterprise AI governance or responsible AI initiatives\nExperience with event-driven architectures, streaming analytics, or operational AI systems\nExperience supporting large-scale data modernization or enterprise analytics transformation efforts\nExperience working within DevSecOps-enabled AI/ML delivery environments\n#DICE #Linkedin\n___________________________________________________________________________________________________________\nHere at Revolutional we are pleased to have been repeatedly recognized for our outstanding work culture, the innovative work we do, and the employees on our team who make a difference each day. Some of these recognitions include: \nRecognized as a Top 20 \"Best Place to Work in Virginia\"\nRecipient of Department of Labor's HireVets Gold Medallion\nGreat Place to Work Certification for five years running\nA Virginia Chamber of Commerce Fantastic 50 company\nA Northern Virginia Technology Council Tech 100 company \nInc. 5000 list of fastest growing companies for eleven years\nTwo-time SBA SBIR Tibbett's Award winner\nVirginia Values Veterans (V3) Certification\nWe recognize that every bit of our success is the result of our teams of hard-working, motivated, and innovative professionals who are proud to call themselves part of the Revolutional family! In addition to competitive compensation, a family-focused culture, and a dynamic, productive work environment, we offer all full-time employees a variety of benefits including, but not limited to\nTraditional and HSA- eligible medical insurance plans \n100% employer-paid dental and vision insurance options \n100% employer-sponsored STD, LTD, and life insurance\n5% 401(k) company matching\nFlexible-schedules and teleworking options\nPaid holidays and PTO Accrual Plans\nPaid Parental Leave\nProfessional development and career growth opportunities \nTeam and company-wide events, recognition, and appreciation-- and so much more! \nCheck out our Revolutional | LinkedIn to find out a little more about who we are and if we are the right next step for your career! \nRevolutional is an Equal Opportunity Employer providing equal employment opportunity to all employees and applicants for employment without regard to race, color, religion, national origin, age, gender, gender identity, sexual orientation, disability, or genetics. Revolutional does and will take affirmative action to employ and advance in employment individuals with disabilities and protected veterans. To perform the above job successfully, an individual must possess the knowledge, skills, and abilities listed; meet the education and work experience required; and must be able to perform each essential duty and responsibility satisfactorily. Other duties in addition to those listed may be assigned as necessary to meet business needs. Reasonable accommodation will be made to enable an applicant with a disability to successfully apply for and/or perform the essential duties of the job. 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