Lead Data Scientist

我們做什麼

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。

我們是誰

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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Who We Are

At Kenvue, we realize the extraordinary power of everyday care. Built on over a century of heritage and rooted in science, we’re the house of iconic brands - including NEUTROGENA®, AVEENO®, TYLENOL®, LISTERINE®, JOHNSON’S® and BAND-AID® that you already know and love. Science is our passion; care is our talent. Our global team is made by 22,000 diverse and brilliant people, passionate about insights, innovation and committed to deliver the best products to our customers. With expertise and empathy, being a Kenvuer means to have the power to impact life of millions of people every day. We put people first, care fiercely, earn trust with science and solve with courage – and have brilliant opportunities waiting for you! Join us in shaping our future–and yours. 

What You Will Do 

The Data Scientist will lead the Data Science/AI/ML work, drive advanced analytics initiatives, and contribute to the strategic vision of data-driven decision-making within the organization. You will collaborate with cross-functional teams, including data engineers, business analysts, and product managers, to develop innovative data solutions and insights that impact business outcomes positively. With a focus on applying operations research techniques to solve business problems, you will be a hand-on contributor for the data science team, driving advanced analytics initiatives to deliver innovative solutions.

 Responsibilities:

• Technical contribution: Provide technical expertise to the data science team collaborating with data scientists on projects and methodologies. Lead and manage complex data science projects from ideation to implementation, ensuring timely delivery and high-quality outcomes.
• Modeling and Analysis: Develop and deploy sophisticated simulation and optimization model using open source and commercial solvers.
• Data Exploration: Conduct in-depth exploratory data analysis to understand patterns, trends, and anomalies that can lead to valuable business insights.
• Algorithm Selection and Analytic formulation: Identify and recommend appropriate machine learning algorithms and techniques for specific business problems.
• Innovation and Research: Stay up-to-date with the latest advancements in Operations Research and apply cutting-edge techniques to enhance analytical capabilities.
• External partner engagement: Evaluation and selection of external vendors partners for data science and machine learning. Working closely with the selected partner to oversee the technical and business outcomes.
• Collaboration: Collaborate with stakeholders to understand business challenges, align data science initiatives with business goals, and communicate results effectively.
• Data Governance and Ethics: Ensure compliance with data governance policies, privacy regulations, and ethical considerations related to data science projects.
• Continuous Improvement: Promote a culture of continuous learning and improvement within the data science team, encouraging the adoption of best practices and innovative approaches.

Key Accountabilities:

• Collect and clean data
• Build and train models
• Interpret and communicate results
• Work with stakeholders to understand their needs
• Deploy models into production
• Maintain and improve models
• Developing data pipelines
• Building data visualizations
• Writing data science reports
• Presenting data science findings to stakeholders
• Collaborating with other data scientists and engineers
• Creating data mining architectures/models/protocols, statistical reporting, and data analysis methodologies to identify trends in large data sets
• Analysis may be applied to various areas of the business (e.g., Market Economics, Supply Chain, Marketing/Advertising, Scientific Research, etc.)
• Researching and applying knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions

What We Are Looking For 

Required Qualifications:

• Strong knowledge and understanding of Probability & Statistics
• University/Bachelor's degree in Computer Science, Statistics, or a related field.
• 7-9 years of experience in data analysis, machine learning, or a related field.
• Proven experience (typically 6+ years) in Data Science/AI/ML, with a strong track record of leading and delivering successful Data Science/AI/ML projects.
• Sound knowledge of Data Science/AI/ML concepts and techniques from Regression, Clustering, Classification, Time series, Deep learning, Gen AI, Statistics and Probability
• Proficiency in at least one commonly used coding language preferably Python.
• Experience with big data technologies and frameworks (e.g., Spark) is a plus.
• Excellent problem-solving and analytical skills, with a keen eye for identifying patterns and insights in complex datasets.
• Strong communication skills and the ability to present technical findings to both technical and non-technical stakeholders.
• Business acumen and the ability to align data science projects with organizational goals and objectives.

Desired Qualifications:

• Proficiency in one of the following areas: Linear Algebra, Calculus, preferably from Retail, eCommerce or CPG industry

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