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Principal Data Scientist

2026-10-29

Japan, Tokyo-to, Tokyo

3 days / week in-office

Overview <div>Microsoft Frontier Company Engineering チームでは、単にソフトウェアを構築するだけではありません。世界で最も複雑な組織の一部に対して、実際の成果を届けることが私たちの仕事です。 </div><div>私たちは世界トップクラスのエンジニアで構成されるグローバルチームであり、10年以上にわたり Forward Deployed Engineering（FDE）モデルで活動してきました。お客様のチームに直接入り込み、肩を並べて最も困難な課題を解決し、本番運用可能なソリューションを数か月ではなく数日で提供しています。 </div><div>データサイエンティストとして、組織におけるデータ活用のあり方の変革を支援していただきます。モデルを開発し、実験を行い、ビジネスに測定可能なインパクトをもたらすエビデンスに基づく意思決定を推進します。エンジニア、プロダクトマネージャー、ドメインエキスパートとともに少人数の多職種チームで働き、データの探索からソリューションのデプロイまで、ライフサイクル全体を担います。 </div><div>私たちの仕事は AI によって支えられています。開発ライフサイクル全体に AI のマインドセットとツールを取り入れ、セキュリティ、品質、信頼性において最高水準を維持しながら、アイデアから本番環境まで数日で到達します。 ーーー In 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.</div> We 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.As 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.Our 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. Responsibilities <div>ビジネス理解とインパクト：</div><div>専門知識を活かしてプロジェクトが直面する問題や課題を分析し、製品ライン全体にわたって最終的な成果に影響し得る要因を明らかにし、管理し、緩和する。ビジネスチームと連携して戦略を推進し、改善策を提言する。新たな業務機会や、既存の成果を別の文脈で活用する機会を提起する。標準とベストプラクティスを確立・適用し、他者に教える。 </div><div>データの準備と理解：</div><div>データ取得の取り組みを統括し、データが適切に整形され、正確に記述されていることを保証する。データ探索に必要な主要技術・ツール（SQL、Python など）を活用する。クエリ、可視化、レポーティングの手法を用いて、主要属性の分布、属性間の関係、単純な集計、重要なサブグループの特性、統計分析などを含むデータ探索を行う。データクレンジングと分析のベストプラクティスについてエンジニアを指導・コーチングする。既存データセットのギャップを特定し、新たなデータセット（サードパーティのデータセットなど）の導入を推進する。データの収集・準備に関わる倫理およびプライバシーポリシーについての議論を主導する。業界全体の倫理に関する知見やベストプラクティスを取り入れ、社内プロセスに影響を与え、意思決定を推進する。製品横断でデータプラットフォームをゼロから構築する。既存の技術、製品、ソリューション、および確立されたパターンやプラクティスを用いて、データサイエンスのビジネスソリューションを構築する。データサイエンティストが作成したモデルの運用化について指針を示す。データから新たな機会を見出し、汎用的に利用できる形でデータを処理する。データの取得と理解に関するベストプラクティスについて、ソートリーダーシップおよび知的財産（IP）の蓄積に積極的に貢献する。データ整合性の問題を主導して解決する。 </div><div>モデリングと統計分析：</div><div>機械学習（ML）ソリューションを、他者が利用できる再利用可能なフレームワーク（モジュール、パッケージ、汎用ソフトウェアなど）へと汎用化する。バイアス、プライバシー、倫理に関するチームの基準を自ら体現し、徹底させる。チームメンバーのモデルの手法とパフォーマンスを評価し、必要に応じて改善策を提言する。データリーケージ、バイアスとバリアンスのトレードオフ、手法上の限界などのリスクを予見し、チームメンバーを解決策へと導く。モデルの検証、実装、適用に関するベストプラクティスを推進する。大規模に稼働する運用モデルを開発する。他者と連携し、ML および予測分析の適用機会を特定・探索する。ML モデリングによって変革的なカスタマーソリューションを生み出す新たな顧客機会を特定する。AI 倫理に配慮した ML モデリングのベストプラクティスを取り入れる。AI および ML における最新・新興の手法を常に把握し、専門領域において深い専門性を築く。 </div><div>評価：</div><div>データ分析およびモデリング手法を徹底的にレビューし、プロセスレビューを総括するとともに、見落とされている点や再検討が必要な点を明らかにする。評価とプロセスレビューの結果を活用し、次のステップ（デプロイ、さらなるイテレーション、新規プロジェクトなど）を決定する。新たな評価アプローチや指標を見出し、モデルを評価するための新しい手法を考案する。 </div><div>業界・研究知識／機会の特定： </div><div>産業界と学術界の進展を追い、関連する最先端の研究を特定し、アルゴリズムや手法を応用してイノベーションを推進し、新たなソリューションを開発する。業界のトレンド、技術、進展を調査し、深い知識を維持する。チーム内の取り組みに関する知見を活かし、協業を提案する。市場の強み、弱み、機会、脅威、トレンドに対する戦略的な対応を主体的に策定する。経験の浅いエンジニアに対し、データ分析のベストプラクティスについて指導・コーチングを行う。経験の浅いエンジニアにとっての専門家（SME）およびロールモデルとしての役割を果たす。戦略上の機会を特定する。外部カンファレンスへの積極的な参加を通じて、ソートリーダーシップおよび知的財産（IP）に関するベストプラクティスの蓄積に積極的に貢献する。 </div><div>コーディングとデバッグ：</div><div>複数の機能／ソリューションにまたがる、効率的で可読性・拡張性の高いコード／モデルを自律的に記述する。実装と改善に関するフィードバックや提案を通じて、コード／モデルのレビュープロセスに貢献する。エラーや欠陥の特定、切り分け、解決など、適切なモデリング、コーディング、デバッグの手法について専門性を高める。エラーを適切にトラブルシューティングするため、複数の情報源からのデータ／情報の収集・統合・解釈においてプロジェクトチームを主導する。最適化されていない機能／ソリューションについてプロダクトグループにフィードバックし、新機能の可能性を探る。Hadoop エコシステム、Apache Spark、継続的インテグレーション／継続的デリバリー（CI/CD）、Docker、Delta Lake、MLflow、AML、REST API の利用・開発など、ビッグデータのソフトウェアエンジニアリングの概念に関するエキスパートレベルの能力を活用する。 </div><div>ビジネスマネジメント：</div><div>ビジネス戦略、顧客戦略、ソリューション戦略の目標を定義する。チームと連携し、機械学習（ML）やその他のデータサイエンスツールの適用機会を特定・探索する。技術的な専門性を活かし、製品チーム、営業チーム、エリアチーム、サービス部門の間のパートナーシップを構築する。分野を越えて協働する。知的財産（IP）の定義の改善を主導する。経験の浅いエンジニアをコーチング・メンタリングする。 </div><div>顧客／パートナー志向：</div><div>顧客のニーズと視点を受け止め、その視点を尊重し、より広い顧客組織や状況に目を向け、信頼されるアドバイザーとして行動することで、顧客志向を徹底する。ビジネス、製品／サービスの機能、データソース、問題を捉え直すための方法論、そして顧客の視点への理解を組み合わせて機会を見出し、価値ある洞察を提供する。結果を解釈して洞察を導き出し、顧客に効果的に伝える。顧客との議論をリードし、データ上の制約を踏まえて実現可能な、実践的なソリューションを提示する。 </div><div>その他：</div><div>当社のカルチャーと価値観を体現する。 ーーーー Business Understanding and Impact: Leverages subject matter expertise to analyze problems and issues facing projects to uncover, manage, and/or mitigate factors that can influence final outcomes across product lines. Partners with business team to drive strategy and recommend improvements. Raises opportunities to look for new work opportunities and different contexts to use existing work. Establishes, applies, and teaches standards and best practices.</div>Data Preparation and Understanding: Oversees data acquisition efforts and ensures data is properly formatted and accurately described. Utilizes key technologies and tools necessary for data exploration (e.g., structured query language [SQL], Python). Uses querying, visualization, and reporting techniques to explore the data, including distribution of key attributes, relationships between attributes, simple aggregations, properties of significant sub-populations, and statistical analyses. Mentors and coaches engineers in data cleaning and analysis best practices. Identifies gaps in current data sets and drives onboarding of new data sets (e.g., bringing on third-party data sets). Drives discussions around ethics and privacy policies related to collecting and preparing data. Integrates industry-wide ethics insights and best practices to influence internal processes and drive decision-making. Builds data platforms from scratch across products Builds data-science business solutions using existing technologies, products, and solutions, as well as established patterns and practices. Provides guidance on model operationalization of models created by data scientists. Identifies new opportunities from data and processes data in a way that is usable for general purpose. Actively contributes to the body of thought leadership and intellectual property (IP) on best practices for data acquisition and understanding. Leads and resolves data-integrity problems.Modeling and Statistical Analysis: Generalizes machine learning (ML) solutions into repeatable frameworks (e.g., modules, packages, general-purpose software) for others to use. Exemplifies and enforces team standards related to bias, privacy, and ethics. Evaluates the methodology and performance of teammates’ models and, as appropriate, recommends solutions for improvement. Anticipates the risks of data leakage, the bias/variance tradeoff, methodological limitations, etc., and is able to guide teammates on solutions. Drives best practices relative to model validation, implementation, and application. Develops operational models that run at scale. Partners with others to identify and explore opportunities for the application of ML and predictive analysis. Identifies new customer opportunities for driving transformative customer solutions with ML modeling. Incorporates best practices for ML modeling with consideration for artificial intelligence (AI) ethics. Develops deep expertise in specialized areas by staying abreast of current and emerging methodologies an AI and ML.Evaluation: Conducts thorough review of data analysis and modeling techniques used to summarize the process review and highlight areas that have been missed or need reexamining. Utilizes results of the assessment and process review to decide on next steps (e.g., deployment, further iterations, new projects). Identifies new evaluation approaches and metrics and invents new methodologies to evaluate models.Industry and Research Knowledge/Opportunity Identification: Tracks advances in industry and academia, identifies relevant state-of-the-art research, and adapts algorithms and/or techniques to drive innovation and develop new solutions. Researches and maintains deep knowledge of industry trends, technologies, and advances. Leverages knowledge of work being done on team to propose collaboration efforts. Proactively develops strategic responses to specific market strengths, weaknesses, opportunities, threats, and/or trends. Mentors and coaches less experienced engineers in data analysis best practices. Serves as subject matter expert and role model for less experienced engineers. Identifies strategy opportunities. Actively contributes to the body of thought leadership and intellectual property (IP) best practices by actively participating in external conferences.Coding and Debugging: Independently writes efficient, readable, extensible code/model that spans multiple features/solutions. Contributes to the code/model review process by providing feedback and suggestions for implementation and improvement. Develops expertise in proper modeling, coding, and/or debugging techniques such as locating, isolating, and resolving errors and/or defects. Leads a project team in the gathering, integrating, and interpreting of data/information from multiple sources in order to properly troubleshoot errors. Provides feedback on non-optimized features/solutions back to product group, and explores potential for new features. Leverages expert-level proficiency of big-data software engineering concepts, such as Hadoop Ecosystem, Apache Spark, continuous integration and continuous delivery (CI/CD), Docker, Delta Lake, MLflow, AML, and representational state transfer (REST) application programming interface (API) consumption/development.Business Management: Defines business-strategy goals, customer-strategy goals, and solution-strategy goals. Partners with teams to identify and explore opportunities for the application of machine learning (ML) and other data-science tools. Leverages technical expertise to develop partnerships between product teams, Sales teams, Area teams, and Services. Work collaboratively across disciplines. Leads involvement of intellectual property (IP) definition improvement. Coaches and mentors less experienced engineers.Customer/Partner Orientation: Commits to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer organization/context, and serving as a trusted advisor. Identifies opportunities and adds valuable insight by incorporating an understanding of the business, product/service functionality, data sources, methodologies to reframe problems, and the customer perspective. Interprets results, develops insights, and effectively communicates results to the customer. Leads the discussion with customers and offers pragmatic solutions that are feasible given their data limitations. Other: Embody our culture and values Qualifications <div>必須要件 </div><div><ul style="list-style-type: disc;"><li>データサイエンス、数学、統計学、計量経済学、経済学、オペレーションズリサーチ、コンピュータサイエンス、または関連分野の学士号、かつ10年以上のデータサイエンス経験（構造化・非構造化データの管理、統計手法の適用と結果の報告など） </li></ul></div><div><ul style="list-style-type: disc;"><li>または、同分野の修士号、かつ7年以上のデータサイエンス経験（構造化・非構造化データの管理、統計手法の適用と結果の報告など） </li></ul></div><div><ul style="list-style-type: disc;"><li>または、同分野の博士号、かつ5年以上のデータサイエンス経験（構造化・非構造化データの管理、統計手法の適用と結果の報告など） </li></ul></div><div><ul style="list-style-type: disc;"><li>または、これらと同等の経験 </li></ul></div><div><ul style="list-style-type: disc;"><li>日本語と英語の両方でビジネスレベル以上の語学力 </li></ul></div><div>歓迎要件 </div><div><ul style="list-style-type: disc;"><li>データサイエンス、数学、統計学、計量経済学、経済学、オペレーションズリサーチ、コンピュータサイエンス、または関連分野の学士号、かつ12年以上のデータサイエンス経験（構造化・非構造化データの管理、統計手法の適用と結果の報告など） </li></ul></div><div><ul style="list-style-type: disc;"><li>または、同分野の修士号、かつ10年以上のデータサイエンス経験（構造化・非構造化データの管理、統計手法の適用と結果の報告など） </li></ul></div><div><ul style="list-style-type: disc;"><li>または、同分野の博士号、かつ8年以上のデータサイエンス経験（構造化・非構造化データの管理、統計手法の適用と結果の報告など） </li></ul></div><div><ul style="list-style-type: disc;"><li>または、これらと同等の経験 </li></ul></div>ーーー Required/Minimum Qualifications: 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 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 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 equivalent experience. Business-level or higher proficiency in both Japanese and English is required. Additional or Preferred Qualifications: 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 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 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 equivalent experience. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. <hr> Microsoft 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 <a href="https://careers.microsoft.com/v2/global/en/accessibility.html">requesting accommodations.</a>

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Senior Product Designer, AI Experience

2026-10-30

Japan, Tokyo-to, Tokyo

1 day / week in-office

Overview <div>Do you have a passion to work with customers on their most forward-looking AI initiatives? We are seeking someone interested in researching the impact of, and designing for the human experience in solutions supported by AI. </div><div>Microsoft Frontier Company is a global organization that works directly with customers looking to leverage the latest technologies to address their toughest challenges. We are lucky enough to research, design & develop with customers to collaboratively innovate solutions tailored to their business needs. In the process, we help shape the future of our own platforms by partnering with our product groups to improve Microsoft product experiences. Our diverse skillsets and curious natures help us foster innovation with our customers and with each other. Fresh perspective is part of how we create meaningful impact in our work and inclusive day-to-day experiences. </div><div>We are looking for a Senior Product Designer for AI-powered products and solutions with strong expertise in human-centered design (HCD), design research, and product design to join our expanding, client facing team. The ideal candidate brings solid product design judgment and is comfortable working with data and AI driven systems, using insights from userresearch, experimentation, and system behavior to inform design decisions. </div><div>You will contribute to the design of AI‑enabled experiences where data science and machine learning are core to the solution, working closely with customers as well as Data Scientists, Technical Program Managers, and Software Engineers. This role requires comfort working in complex and evolving problem spaces, collaborating to clarify requirements and translate AI capabilities into experiences that deliver human value and business impact. You will be hands‑on in design and prototyping, bringing production-level design quality contributing to experience quality across projects. </div> Responsibilities <div><div>Product Design (Customer facing AI solutions)</div><div><ul style="list-style-type: disc;"><li>Design and deliver high‑quality, AI‑enabled user experiences from concept through detailed execution, within a defined problem space </li></ul></div><div><ul style="list-style-type: disc;"><li>Apply human-centered design and research insights to inform interaction, visual, and system level design decisions </li></ul></div></div><div><div><ul style="list-style-type: disc;"><li>Plan and conduct qualitative and quantitative research such as user testing, synthesizing findings into clear insights that inform design solutions </li></ul></div><div><ul style="list-style-type: disc;"><li>Create effective production-quality design artifacts d including flows, prototypes, and visualizations that communicate ideas and support decision making, and drive products toward successful delivery </li></ul></div><div> Design Collaboration</div><div><ul style="list-style-type: disc;"><li>Collaborate closely with Technical Program Managers, Software Engineers, Data Scientists, and other designers to shape and deliver solutions </li></ul></div><div><ul style="list-style-type: disc;"><li>Contribute design perspectives within multidisciplinary teams, advocating for user needs and experience quality </li></ul></div><div><ul style="list-style-type: disc;"><li>Incorporate feedback from customers, partners, and teammates to iteratively improve designs </li></ul></div><div><ul style="list-style-type: disc;"><li>Ensure designs align with responsible AI principles and established experience standards </li></ul></div></div> Qualifications <div><div><ul style="list-style-type: disc;"><li>Business-level or higher proficiency in both written and spoken Japanese and English is required </li></ul></div><div><ul style="list-style-type: disc;"><li>Working knowledge of responsible AI principles or other relevant considerations,　and experience contributing to the design of AI‑enabled products or services </li></ul></div><div><ul style="list-style-type: disc;"><li>Solid grounding in human-centered design and design research, with hands-on experience applying qualitative and quantitative methods to inform product decisions </li></ul></div><div><ul style="list-style-type: disc;"><li>Strong product design skills, with the ability to translate research findings, data, and feedback into clear insights and well-crafted user interactions </li></ul></div><div><ul style="list-style-type: disc;"><li>Proficiency in prototyping and iterative design, including Figma, with experience producing low to high-fidelity artifacts to explore and validate ideas </li></ul></div><div><ul style="list-style-type: disc;"><li>Comfort working in ambiguous problem spaces with guidance </li></ul></div><div><ul style="list-style-type: disc;"><li>Effective cross‑disciplinary collaborator, able to work closely with designers, engineers, data scientists, and product partners to advocate for user needs and experience quality </li></ul></div><div><ul style="list-style-type: disc;"><li>Experience working directly with enterprise customers or clients in complex, ambiguous problem spaces </li></ul></div><div>Preferred qualifications </div><div> </div></div><div><div><ul style="list-style-type: disc;"><li>Degree in Product Design, Human Computer Interaction, Information Design, User Experience, Interaction Design or related field AND 5+ years of experience working in product, consulting or service design OR equivalent experience (e.g., hands-on experience designing, prototyping, and shipping digital products). </li></ul></div><div><ul style="list-style-type: disc;"><li>Industry experience working across one or multiple product stages </li></ul></div><div><ul style="list-style-type: disc;"><li>Experience working as part of geographically dispersed, diverse, and virtual teams </li></ul></div></div> This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. <hr> Microsoft 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 <a href="https://careers.microsoft.com/v2/global/en/accessibility.html">requesting accommodations.</a>

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Cloud ＆ AI Specialist (Azure Sales for I&M Energy Major)

2026-10-28

Japan, Tokyo-to, Tokyo

1 day / week in-office

Overview 大手エネルギー業界（電力/ガス）顧客むけのAzureを中心としたクラウドセールスのポジションです。 Azure Solution Specialistとして、チームのSolution engineerと協業し顧客関係者や意思決定者とのディスカッションをリードし、販売機会を特定、適格化、優先順位付け、加速化することが求められます。 具体的には以下のような活動が求められます。 ①AIを活用したマーケットインテリジェンスツールでトレンドとインサイトを評価し、ホワイトスペース分析を活用し、担当市場領域内のビジネスチャンスとマーケットギャップを特定する。②ソリューション領域と市場を評価し、AIを活用した予測分析によって将来の市場ニーズを予測しながら、顧客のビジネス優先順位と成果に合わせた営業活動を行うための知見を得る。 ③組織横断的に他者と協力し、最先端のAIテクノロジーとクラウドサービスの統合に重点を置きながら、地域内の既存および新規顧客のAIおよびクラウド主導の変革を可能にするソリューションの開発をサポートする。 ④予測精度と売上目標の達成を推進するため、社内のステークホルダーと営業パイプラインのレビューに関与し、AIを活用したアナリティクスと予測ツールを活用して精度を高める。 ⑤各顧客のセキュリティの優先事項に合わせた販売戦略を推進し、安全でAIを活用した変革に対するマイクロソフトの総合価値を示し、顧客のビジネスの成功に貢献する。 Responsibilities Customer Engagement Ensures teams adhere to sales frameworks and guidelines to assess and qualify sales opportunities, ensuring alignment with AI-enhanced sales methodologies and best practices. Leverages expertise in strategy development to empower teams in securing complex, high-value deals. Drives collaboration across organizations (e.g., Account Team Unit [ATU], CSU, ISD, GPS) to lead deal orchestration and ensure effective handoffs throughout the deal lifecycle. Coaches team on advancing best practices to obtain customer commitment, secure deals, and reduce exposure to risks that impacts sales success across the territory. Coaches team on leading the sales strategy tailored to each customer's security priorities, showcasing Microsoft's dedication to secure, AI-powered transformation and addressing their specific needs within the customer success plan, fostering long-term partnerships through AI-driven insights. Leads partner teams, resources and fosters lasting relationships that activate co-selling strategies and drive partner attach to each opportunity through every stage in the sales lifecycle. Leads team on leading partner organization connections (i.e. GPS) that lead to enduring relationships, share gains, partner health and alignment with execution plans to accelerate customer value realization at scale. Sales & Pipeline Management Sets the direction for business analysis and the emerging opportunities to refine the customer portfolio and foster customer innovation across multiple teams. Advocates for the adoption of technologies (e.g., AI sales agents, automation, Power Platforms) to drive growth across the territory. Provides strategic direction and guidance across teams on integrating propensity, renewal, consumption, and usage data to prioritize sales strategy. Directs teams in refining partner engagement for each account and/or opportunity, ensuring seamless handoffs with other teams (e.g., Global Partner Solutions [GPS], Customer Success Unit [CSU], Industry Solutions Delivery [ISD], Partner) throughout the deal lifecycle. Leads teams on leading sales pipeline reviews across the territory with internal senior stakeholders to drive forecasting accuracy and meeting sales targets, ensuring the use of AI-powered analytics and forecasting tools to enhance precision. Leads team on maintaining sales and/or consumption pipeline hygiene on all opportunities and milestones using all available tools and processes. Empowers teams to maintain usage and/or consumption pipeline hygiene to actively monitor adoption trends, identify opportunities for intervention, enabling customers to realize the value of solutions purchased, drive expansion, and ensure healthier, more predictable renewals. Sales Strategy Leads team in comprehensively evaluating of territory and crafts strategic insights to align sales initiatives with customer business priorities and outcomes, incorporating AI-driven predictive analytics to forecast future market needs. Empowers teams to drive cross-functional collaboration to propose solutions and strategies that resonate with and drive customer business objectives. Drives the identification and resolution of gaps, enhancing market engagement and maximizing sales execution. Leads teams in the development and implementation of solutions to enable artificial intelligence (AI)- and cloud-driven transformations for existing and new customers across the territory, emphasizing the integration of cutting-edge AI technologies and cloud services. Acts as a resource for and drives team on crafting and refining strategies and engaging with customers to distinguish Microsoft’s offerings in the competitive landscape. Leads team on acting as a subject matter expert and trusted advisor for strategic customers and orchestrating the adoption of innovative technologies and solutions that align with their goals align and advance their strategic goals and drive digital transformation. Sets strategy for teams on whitespace analysis and identifying business opportunities and market gaps within the assigned territory, utilizing AI-driven market intelligence tools to assess trends and insights. Translates and provides guidance on complex market intelligence, trends, and insights across multiple teams. Leads team in refining and evolving market analysis methodologies to ensure proactive alignment with strategic directives and evolving market trends. Leads and mentors multiple teams in discussions with senior stakeholders and decision makers for high-value customers to deepen relationships and identify, qualify, and accelerate sales opportunities. Serves as a key point of contact and ensures strategic collaboration with internal senior stakeholders within and across organizations to maximize customer success. Directs partnerships with account teams and customers to discuss the use of technological advancements for market influence. Champions and reinforces security principles in customer interactions, opportunity, and pursuits to uphold trust and compliance standards. Models for and coaches team on, and develops a team consumption/usage strategy for driving seller behaviors that include support solutions in every solution sale in collaboration cross organizationally as part of rhythms and scrums. Qualifications Required/minimum qualifications Bachelor's Degree in Computer Science, Information Technology, Business Administration, Information Security, or related field AND 6+ years experience in technology-related sales or account management OR equivalent experience. This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled. <hr> Microsoft 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 <a href="https://careers.microsoft.com/v2/global/en/accessibility.html">requesting accommodations.</a>

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