{"id":3727740,"url":"https://alion.io/job/gptw-us-remote-data-scientist-iv","title":"[Remote] Data Scientist IV","company":{"id":48501,"name":"gptw_us","domain":"greatplacetowork.com","url":"https://alion.io/company/gptw-us","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Recruitee","truth_index":{"grade":"B","score":75,"open_postings":5,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-11-09T06:03:00Z"}},"role":"Data Science","role_family":"Data Science","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["United States"],"countries":["US"],"hiring_countries":["US"],"hiring_countries_total":1,"salary":{"min":154000,"max":219000,"currency":"USD","period":"year","gross":null,"usd_annual":219000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"SQL","optional":false}],"status":"closed","first_seen_at":"2026-11-04T05:50:07Z","employer_posted_date":null,"last_verified_at":"2026-11-04T12:26:41Z","board_verified":false,"closed_at":"2026-11-04T12:26:41Z","days_open":0,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":0},"description":"Note: The job is a remote job and is open to candidates in USA. Great Place To Work is hiring a Data Scientist IV to modernize the systems, methodologies, and workflows behind its Best Workplaces lists and research programs. The role develops and maintains analytical solutions, improves data and list-production processes, and partners with global stakeholders to ensure solutions are scalable, reliable, and credible.\n\nResponsibilities\nIndependently lead complex data science and technical-improvement projects from problem definition through implementation, delivering measurable improvements in business impact, efficiency, quality, scalability, and risk reduction\nDevelop, validate, document, and maintain the algorithms, scripts, statistical models, benchmarks, and data workflows used to produce global Best Workplace lists, independently diagnosing issues and making sound technical decisions related to data preparation, quality assurance, reproducibility, sensitivity testing, and methodology enhancements\nAssess end-to-end list-production and global data-management workflows and lead improvements via automation, standardization, simplification, and scalable system solutions\nTranslate business and methodology needs into implementation-ready requirements, including process maps, data definitions, acceptance criteria, dependencies, test scenarios, controls, and measures of success; proactively resolve conflicting stakeholder needs and surface decisions, tradeoffs, and risks\nDesign and implement AI-enabled solutions, prototypes, and automations, independently determining the appropriate technical approach and partnering with Product, Tech, and business stakeholders when solutions require production engineering, infrastructure, system integration, or secure access\nEnsure technical solutions remain reliable and sustainable by establishing appropriate documentation, testing, monitoring, support, and maintenance practices\nBuild alignment across technical and non-technical stakeholders by clarifying priorities, roles, tradeoffs, risks, and decisions, and by communicating technical concepts in accessible business language\nCross-train with the Principal Data Scientist to maintain coverage during peak periods\n\nSkills\n5-7+ years of professional data science experience, with advanced expertise in machine learning, statistical modeling, algorithms, data transformation, AI-enabled solutions, and the development of applied insights or analytics-based solutions for business users\nAdvanced programming proficiency in Python, along with advanced SQL experience, including querying, reconciling, transforming, and validating large, complex, or incomplete datasets across relational, cloud, or other data platforms\nExperience independently designing, automating, and supporting complex, business-critical data workflows, including APIs, data pipelines, cloud environments, workflow-automation tools, inherited code, and deployed AI-enabled solutions, with the judgment to make progress despite ambiguity or incomplete information\nExperience owning the lifecycle of an internal analytical product or business-critical technical capability, from discovery and requirements through implementation, adoption, maintenance, enhancement, and retirement\nExperience building data science or analytics solutions with production-readiness in mind, including applying software-engineering best practices (such as clean and modular code, version control, automated testing, code review, deployment, monitoring, model-performance and accuracy evaluation, safe change practices, third-party API updates, and troubleshooting production issues) or partnering with software engineers to turn prototypes into reliable, supported production solutions\nExperience eliciting, analyzing, reconciling, and documenting business, functional, technical, data, and integration requirements, including process maps, workflow specifications, data definitions, user stories or use cases, acceptance criteria, test scenarios, and implementation documentation that technical and non-technical partners can use\nStrong systems thinking, initiative, technical judgment, and problem-solving skills, with a demonstrated ability to independently structure complex problems, identify root causes and improvement opportunities, define future-state processes, make well-reasoned recommendations, and determine when to build directly, maintain an interim solution, or partner with Product and Tech\nDemonstrated stakeholder-management, communication, and project-leadership skills, including the ability to build credibility with diverse partners; align stakeholders with different perspectives and priorities; clarify decision rights and ownership; manage expectations, dependencies, and competing demands; communicate progress, risks, and tradeoffs proactively; translate complex technical concepts for senior leaders and non-technical users; and work effectively in a collaborative remote environment while demonstrating commitment to Great Place To Work values, behaviors, and mission\nWorking with survey, employee experience, customer experience, market research, or other human-subjects data, particularly where sampling, measurement, benchmarking, or interpretation matter\nDeveloping scoring, benchmarking, ranking, classification, or eligibility methodologies where analytical decisions have meaningful consequences for customers or other external stakeholders\nWorking with messy, multi-source organizational or entity-level data, including record matching, entity resolution, data reconciliation, validation, and quality assurance\nWorking in consulting, research, professional services, or another client-facing analytical environment, with experience translating ambiguous business questions into rigorous analytical solutions\nModernizing legacy analytical processes or inherited code, including reducing manual work and key-person dependencies while maintaining continuity and accuracy\nUsing R or maintaining/migrating R-based analytical workflows\n\nBenefits\nRemote role.\nEmployees may be eligible to participate in a performance-based bonus plan.\nEmployees may be eligible to receive restricted stock unit awards as part of total compensation.\nWellness programs.\nTuition reimbursement.\nU Choose — a customizable expense reimbursement program that can be used for more than 200+ needs, including student loan repayment, childcare, and pet insurance.\nAn inclusive culture, active and engaged employee resource groups, and caring leaders who value every voice.\n\nCompany Overview\nBuild trust. Drive workplace performance. For all. It was founded in 1992, and is headquartered in Oakland, California, USA, with a workforce of 51-200 employees. Its website is http://greatplacetowork.com.\n\nCompany H1B Sponsorship\nGreat Place To Work has a track record of offering H1B sponsorships, with 1 in 2026. 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