{"id":3469930,"url":"https://alion.io/job/microsoft-principal-data-scientist-9","title":"Principal Data Scientist","company":{"id":18,"name":"Microsoft","domain":"microsoft.com","url":"https://alion.io/company/microsoft","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":82,"open_postings":376,"ghost_share":0,"stale_share":0.71,"repost_share":0.008,"time_to_fill_p50_days":29,"computed_at":"2026-10-31T05:58:55Z"}},"role":"Data Science","role_family":"Data Science","seniority":"lead","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Tokyo, Japan"],"countries":["JP"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":55000,"max_usd":127000,"period":"year","method":"global_role_cell_scaled_by_country","sample_n":771},"experience_years_min":12,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"Delta Lake","optional":false},{"name":"Docker","optional":false},{"name":"Hadoop","optional":false},{"name":"Machine Learning","optional":false},{"name":"MLFlow","optional":false},{"name":"Python","optional":false},{"name":"Rest API","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-10-28T11:23:57Z","employer_posted_date":"2026-10-29","last_verified_at":"2026-10-31T07:40:02Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"OverviewIn the Microsoft Frontier Company Engineering team, you won’t just build software; you’ll deliver real outcomes for some of the world’s most complex organizations.\nWe are a global team of world-class engineers who have been working in a Forward Deployed Engineering (FDE) model for more than a decade, embedding directly within customer teams to solve their toughest challenges, side-by-side, and shipping production-ready solutions in days, not months.\nAs a Data Scientist, you will help transform how organizations use data, developing models, running experiments, and driving evidence-based decisions that have measurable business impact. You’ll work in small, multidisciplinary crews alongside engineers, product managers, and domain experts, owning the full lifecycle from data discovery through to deployed solutions.\nOur work is powered by AI, applying the mindset and tooling across the entire development lifecycle to move from idea to production in days while maintaining the highest standards of security, quality, and trust.\nResponsibilities\nBusiness Understanding and Impact:\nLeverages subject matter expertise to analyze\nproblems and issues facing projects to uncover, manage, and/or mitigate factors\nthat can influence final outcomes across product lines. Partners with business\nteam to drive strategy and recommend improvements. Raises opportunities to look\nfor new work opportunities and different contexts to use existing work.\nEstablishes, applies, and teaches standards and best practices.\nData Preparation and Understanding:\nOversees data acquisition efforts and ensures\ndata is properly formatted and accurately described. Utilizes key technologies\nand tools necessary for data exploration (e.g., structured query language\n[SQL], Python). Uses querying, visualization, and reporting techniques to\nexplore the data, including distribution of key attributes, relationships between\nattributes, simple aggregations, properties of significant sub-populations, and\nstatistical analyses. Mentors and coaches engineers in data cleaning and\nanalysis best practices. Identifies gaps in current data sets and drives\nonboarding of new data sets (e.g., bringing on third-party data sets). Drives\ndiscussions around ethics and privacy policies related to collecting and\npreparing data. Integrates industry-wide ethics insights and best practices to\ninfluence internal processes and drive decision-making. Builds data platforms\nfrom scratch across products Builds data-science business solutions using\nexisting technologies, products, and solutions, as well as established patterns\nand practices. Provides guidance on model operationalization of models created\nby data scientists. Identifies new opportunities from data and processes data\nin a way that is usable for general purpose. Actively contributes to the body\nof thought leadership and intellectual property (IP) on best practices for data\nacquisition and understanding. Leads and resolves data-integrity problems.\nModeling and Statistical Analysis:\nGeneralizes machine learning (ML) solutions\ninto repeatable frameworks (e.g., modules, packages, general-purpose software)\nfor others to use. Exemplifies and enforces team standards related to bias,\nprivacy, and ethics. Evaluates the methodology and performance of teammates’\nmodels and, as appropriate, recommends solutions for improvement. Anticipates\nthe risks of data leakage, the bias/variance tradeoff, methodological\nlimitations, etc., and is able to guide teammates on solutions. Drives best\npractices relative to model validation, implementation, and application.\nDevelops operational models that run at scale. Partners with others to identify\nand explore opportunities for the application of ML and predictive analysis.\nIdentifies new customer opportunities for driving transformative customer\nsolutions with ML modeling. Incorporates best practices for ML modeling with\nconsideration for artificial intelligence (AI) ethics. Develops deep expertise\nin specialized areas by staying abreast of current and emerging methodologies\nan AI and ML.\nEvaluation:\nConducts thorough review of data analysis and\nmodeling techniques used to summarize the process review and highlight areas that\nhave been missed or need reexamining. Utilizes results of the assessment and\nprocess review to decide on next steps (e.g., deployment, further iterations,\nnew projects). Identifies new evaluation approaches and metrics and invents new\nmethodologies to evaluate models.\nIndustry and Research Knowledge/Opportunity Identification:\nTracks advances in industry and academia,\nidentifies relevant state-of-the-art research, and adapts algorithms and/or\ntechniques to drive innovation and develop new solutions. Researches and\nmaintains deep knowledge of industry trends, technologies, and advances.\nLeverages knowledge of work being done on team to propose collaboration\nefforts. Proactively develops strategic responses to specific market strengths,\nweaknesses, opportunities, threats, and/or trends. Mentors and coaches less\nexperienced engineers in data analysis best practices. Serves as subject matter\nexpert and role model for less experienced engineers. Identifies strategy\nopportunities. Actively contributes to the body of thought leadership and\nintellectual property (IP) best practices by actively participating in external\nconferences.\nCoding and Debugging:\nIndependently writes efficient, readable,\nextensible code/model that spans multiple features/solutions. Contributes to\nthe code/model review process by providing feedback and suggestions for\nimplementation and improvement. Develops expertise in proper modeling, coding,\nand/or debugging techniques such as locating, isolating, and resolving errors\nand/or defects. Leads a project team in the gathering, integrating, and\ninterpreting of data/information from multiple sources in order to properly\ntroubleshoot errors. Provides feedback on non-optimized features/solutions back\nto product group, and explores potential for new features. Leverages\nexpert-level proficiency of big-data software engineering concepts, such as\nHadoop Ecosystem, Apache Spark, continuous integration and continuous delivery\n(CI/CD), Docker, Delta Lake, MLflow, AML, and representational state transfer (REST)\napplication programming interface (API) consumption/development.\nBusiness Management:\nDefines business-strategy goals,\ncustomer-strategy goals, and solution-strategy goals. Partners with teams to\nidentify and explore opportunities for the application of machine learning (ML)\nand other data-science tools. Leverages technical expertise to develop\npartnerships between product teams, Sales teams, Area teams, and Services. Work\ncollaboratively across disciplines. Leads involvement of intellectual property (IP)\ndefinition improvement. Coaches and mentors less experienced engineers.\nCustomer/Partner Orientation:\nCommits to a customer-oriented focus by\nacknowledging customer needs and perspectives, validating customer\nperspectives, focusing on broader customer organization/context, and serving as\na trusted advisor. Identifies opportunities and adds valuable insight by\nincorporating an understanding of the business, product/service functionality,\ndata sources, methodologies to reframe problems, and the customer perspective.\nInterprets results, develops insights, and effectively communicates results to the\ncustomer. Leads the discussion with customers and offers pragmatic solutions\nthat are feasible given their data limitations.\nOther:\nEmbody our culture and values\nQualifications\nRequired/Minimum Qualifications\nBachelor's degree in data science,\nMathematics, Statistics, Econometrics, Economics, Operations Research, Computer\nScience, or related field AND 10+ years data-science experience (e.g., managing\nstructured and unstructured data, applying statistical techniques and reporting\nresults)\nOR master's degree in data science,\nMathematics, Statistics, Econometrics, Economics, Operations Research, Computer\nScience, or related field AND 7+ years data-science experience (e.g., managing\nstructured and unstructured data, applying statistical techniques and reporting\nresults)\nOR Doctorate in Data Science, Mathematics,\nStatistics, Econometrics, Economics, Operations Research, Computer Science, or\nrelated field AND 5+ years data-science experience (e.g., managing structured and\nunstructured data, applying statistical techniques and reporting results)\nOR equivalent experience.\nBusiness-level or higher proficiency in both Japanese and English is required.\nAdditional or Preferred Qualifications:\nBachelor's degree in data science,\nMathematics, Statistics, Econometrics, Economics, Operations Research, Computer\nScience, or related field AND 12+ years data-science experience (e.g., managing\nstructured and unstructured data, applying statistical techniques and reporting\nresults)\nOR master's degree in data science, Mathematics, Statistics,\nEconometrics, Economics, Operations Research, Computer Science, or related\nfield AND 10+ years data-science experience (e.g., managing structured and\nunstructured data, applying statistical techniques and reporting results)\nOR Doctorate in Data Science, Mathematics, Statistics,\nEconometrics, Economics, Operations Research, Computer Science, or related\nfield AND 8+ years data-science experience (e.g., managing structured and\nunstructured data, applying statistical techniques and reporting results)\nOR\nequivalent experience.\nThis position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.\nMicrosoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.","description_format":"text","description_chars":10336,"description_truncated":false,"requirements":{"experience_years_min":12,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[{"language":"Japanese","level":"All levels","optional":false},{"language":"English","level":"All levels","optional":false}]},"benefits":[],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Console Games","Cloud Platforms (IaaS & PaaS)","Gaming Consoles","Developer Tools"],"lifecycle":[{"event":"open","at":"2026-10-29T16:39:59Z"}],"visa":[],"liveness":{"score":40,"band":"fade","label":"Fading","p_open":1,"p_active":0.417,"p_room":1,"age_days":2,"expected_fill_days":29,"reasons":["conf:2","stale_co","evergreen","wave","velocity","win:early","comp:brand"],"computed_at":"2026-10-31T05:58:55Z"},"pay":null,"html_url":"https://alion.io/job/microsoft-principal-data-scientist-9","json_url":"https://alion.io/job/microsoft-principal-data-scientist-9.json","meta":{"generated_at":"2026-10-31T08:07:26Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":12134,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-11-01T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":18},"rest":"https://alion.io/mcp/rest/get_company?id=18"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fmicrosoft-principal-data-scientist-9"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fmicrosoft-principal-data-scientist-9"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fmicrosoft-principal-data-scientist-9"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/microsoft-principal-data-scientist-9\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fmicrosoft-principal-data-scientist-9"}],"agent":{"mcp":"https://alion.io/mcp/jobs","mcp_open":"https://alion.io/mcp/open","next":[{"tool":"get_job","arguments":{"id":3469930}},{"tool":"search_jobs","arguments":{"company":"microsoft.com","detail":"compact"}},{"tool":"match_people","arguments":{"job_id":3469930},"note":"people open to offers who fit this vacancy"}],"note":"The same data through MCP tools: https://alion.io/mcp/open needs no sign-in (compact searches, postings, people); https://alion.io/mcp with an Alion account has everything. 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