Kenvue is currently recruiting for:

MANAGER – DATA SCIENCE

This position reports to Senior Manager – Data Science and is based at Bangalore, India or Hybrid.

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® Brand Adhesive Bandages that you already know and love. Science is our passion; care is our talent. Our global team is made up of ~ 22,000 diverse and brilliant people, passionate about insights, innovation and committed to delivering the best products to our customers. With expertise and empathy, being a Kenvuer means having the power to impact the 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. For more information, click here.

Role reports to: Senior Manager, Data Science

Location: Bangalore, India or Hybrid

Travel %: xxx

Pay: xxx (if compliant with country laws)

What you will do 

The Manager – Data Science is responsible for delivering critical insights and intelligence to cross-functional Supply Chain teams through scalable data science solutions. This individual will work with cross-functional subject matter experts (SMEs) to deeply understand business context and key business questions / opportunities, as well as collaborate with other teams (e.g., Digital Capability teams, PMO, IT delivery, Data Engineering, Data Quality, Data Management & Governance) to ensure delivery of scalable data science solutions. 

The ideal candidate for this role will demonstrate a combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypotheses through the discovery phase.

Key Responsibilities

·         Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business questions 

·         Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment and operationalization of projects 

·         Product development across supply chain functions for data Science including cognitive engineering, conversational bots

·         Make solution recommendations that appropriately balance speed to market and analytical soundness, lead service delivery, milestone tracking 

·         Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories.

·         Provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts; make impactful contributions to internal discussions on emerging practices

·         Facilitate cross-geography sharing of new ideas, learnings, and best-practices

·         Deploy algorithms to production to identify actionable insights from large databases.

·         Compare results from various methodologies and recommend optimal techniques. 

·         Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories.

·         Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment 

·         Provide guidance and leadership to more junior data scientists, managing processes and flow of work, vetting designs, and mentoring team members to realize their full potential 

What We Are Looking For

Required Qualifications

·         Masters or PhD in Computer Science, Engineering, or a related field

·         8-12 years of business experience, with at least 8 years of experience as a Data Scientist

·         Advanced knowledge of AI development and architecture, 

·         A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of a project

·         Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages Strong hands-on skills in both feature engineering and hyperparameter optimization

·         Experience in driving large AI projects & conversion to products

·         Experience with Microsoft Azure or AWS data management tools such as Azure Data factory, Azure ML, Synapse, Databricks

·         Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies

·         Experience with deep learning architectures such as GPTs and Transformers

·         Ability to lead, manage, build, and deliver business results through a team of data scientists

·         Excellent written and verbal communications skills to share ideas, data analysis assumptions and results in a clear and compelling manner

·         Self-motivated and a proactive problem solver who can work independently and in teams

Desired Qualifications

·         Experience working in one or multiple supply chain functions (e.g., procurement, planning, manufacturing, quality, logistics) is strongly preferred

·         Experience in applying AI/ML within a CPG or Healthcare business environment is strongly preferred.

·         Experience in supply chain solutions like smart ops, Digital Twin, Inventory Optimization, etc. is preferred.

·         Experience in NLP, Vision, and IOT is preferred

·         Experience in creating CI/CD pipelines for deployment using Jenkins is preferred

·         Experience implementing MLOPs framework and understanding of data security implementations on ML models is preferred

·         Hands on experience developing ML-driven models is preferred

·         Good working knowledge of Agile principle and processes is preferred

Masters or PhD in Computer Science, Engineering, or a related field