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在 Kenvue，我們意識到日常護理的非凡力量。我們以一個多世紀的傳統為基礎，植根於科學，是標誌性品牌的品牌 - 包括您已經熟悉和喜愛的 NEUTRGENA®、AVEENO、TYLENOL®®、LISTERINE®、JOHNSON'S® 和 BAND-AID®。科學是我們的熱情所在;關心就是我們的才能。

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我們的全球團隊由 ~ 22,000 名才華橫溢的員工組成，他們的職場文化中，每個聲音都很重要，每一個貢獻都受到讚賞。 我們熱衷於洞察， 創新並致力於為我們的客戶提供最好的產品。憑藉專業知識和同理心，成為 Kenvuer 意味著每天有能力影響數百萬人。我們以人為本，熱切關懷，以科學贏得信任，以勇氣解決——有絕佳的機會等著您！加入我們，塑造我們和您的未來。有關更多資訊，請按兩下 here.

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Position Overview

The Data Analytics & Solutions team within the Strategy function enables business growth through data-driven decision-making. We are seeking a Business Data Analyst who will support sales performance management, forecasting, customer analytics, and strategic decision-making across the organization.

The team’s core strength remains the use of rich first-party customer and transaction data. Customer and consumer analytics continue to be an important part of the scope, while the role increasingly emphasizes business performance analysis, forecasting, growth opportunity identification, and actionable recommendations for senior leaders and cross-functional stakeholders.

The ideal candidate combines strong business and financial acumen with hands-on analytical capability. Data science knowledge is highly valued, but the primary expectation is to solve business problems with data and influence action, rather than develop advanced models for their own sake.

Key Responsibilities

1. Business Performance Analytics & Planning: Analyze sales and business performance using GTS, NTS, profitability, productivity, and operational KPIs. Support weekly, monthly and annual performance reviews.

•  Support Business Plan (BP), Latest Estimate (LE), and forecast development. Build driver-based forecasts and scenarios, explain gaps versus plan and prior year, and recommend actions.

•  Translate business trends and financial or commercial drivers into clear executive-ready narratives and decision points.

2. Commercial & Growth Analytics: Identify growth opportunities across products, channels, campaigns, and customer segments. Analyze acquisition, conversion, retention, reactivation, basket size/AOV, LTV, and ROI.

•  Evaluate commercial and marketing initiatives through structured measurement, test-and-learn approaches, and post-implementation reviews.

3. Customer & First-Party Data Analytics: Analyze customer purchase behavior and lifecycle trends through cohort, retention, segmentation, LTV, CRM, and activation analyses.

•  Use first-party data as a strategic asset and combine it with digital, media, market, panel, or other external data when relevant.

4. Reporting & Analytics Solutions: Design and maintain dashboards, recurring performance trackers, automated reporting, reusable datasets, and self-service analytics solutions.

•  Improve KPI standardization, metric definitions, data quality, reconciliation, documentation, and governance in partnership with business and technology teams.

5. Business Partnering & Project Delivery: Frame ambiguous business questions, align analytical objectives and success measures, manage priorities and vendors, and deliver recommendations through implementation and measurement.

6. Advanced Analytics: Apply statistics, forecasting techniques, predictive analytics, machine learning, experimentation, or AI-enabled approaches where they create measurable and interpretable business value.

Typical Data and Deliverables

•  First-party customer, transaction, product, promotion, channel, campaign, contact-history, CRM, and digital behavior data.

•  Business planning and performance data, including GTS, NTS, targets, forecasts, margins, trade spend, operational drivers, and management KPIs.

•  Executive-ready performance narratives, variance and root-cause analyses, forecasts, scenarios, opportunity sizing, and recommendations.

•  Dashboards, recurring trackers, analytical datasets, KPI definitions, measurement plans, documentation, and decision logs.

Required Skills and Experience

•  3+ years of experience in Business Analytics, Commercial Analytics, Strategy, CRM Analytics, or a comparable analytical role.

•  Demonstrated experience in sales performance analysis, forecasting, business planning, variance analysis, and management reporting.

•  Working knowledge of commercial finance and accounting concepts, including GTS (Gross Transaction Sales), NTS (Net Trade Sales), gross-to-net drivers,, P&L fundamentals, budget/forecast processes, and ROI.

•  Ability to structure ambiguous business questions, connect analysis with commercial context, and translate findings into actionable recommendations.

•  Hands-on experience with SQL, advanced Excel, and Power BI, Tableau, or equivalent BI platforms.

•  Experience working with large or complex datasets, validating data quality, reconciling figures, and aligning metric definitions across stakeholders.

•  Strong presentation, storytelling, stakeholder management, and cross-functional project coordination skills.

•  Business-level Japanese. English reading and writing are required; business conversation capability is preferred.

Preferred Skills and Experience

•  Experience in D2C, e-commerce, retail, beauty, consumer health, FMCG, or another customer-rich business.

•  Experience with first-party data, CRM, customer segmentation, retention/LTV analysis, digital analytics, campaign measurement, or marketing activation.

•  Working knowledge of Python or R and familiarity with statistics, experimental design, predictive modeling, machine learning, or AI-enabled analytics.

•  Experience with CDPs, cloud data platforms, data warehouses, Snowflake, AWS, or equivalent environments.

•  Experience managing vendors or leading analytical workstreams from problem definition through implementation and adoption.

•  A degree or equivalent experience in a quantitative or business discipline.

Ideal Candidate Profile

•  Business-first and decision-oriented, with strong analytical discipline.

•  Able to connect business context, commercial and financial metrics, customer data, and technology.

•  Clear and influential communicator with both business leaders and technical teams.

•  Pragmatic with analytical methods and focused on measurable business impact.

•  Curious about first-party data and motivated to continue developing data science literacy.

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