Senior Data Scientist

Who we Are ? At Kenvue , we realize the extraordinary power of everyday care. Built on over a century of heritage and rooted in science, were the house of iconic brands - including NEUTROGENA, AVEENO, TYLENOL, LISTERINE, JOHNSONS and BAND-AID that you already know and love. Science is our passion; care is our talent. Our global team is made up with 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 futureand yours. For more information, click here . The Digital Transformation Office is orchestrating our journey to become a Digital First organization by building and deploying end-to-end digital solutions that solve unmet needs and generate value through a fully integrated digital ecosystem. The Analyst, Data Science will deliver 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, ML Ops) 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 hypothesis through the discovery phase of the project and excellent written and communications skills to report back the findings in a clear, structured manner What you will do ? Key Responsibilities: Kenvues DTO, Digital Transformation Office is leading the transformation of operations with deployment of cutting edge digital solution. Demand Sensing and Advanced Forecasting is a key effort within data science team of DTO office. Demand planning master data management is a central activity to drive the forecasting and planning efficiencies. We are looking to set up a central team to take care of master data management activities. This will include PIPO, Baseline management, sales history management and Forecasting Analytics. PIPO is a process to manage the product lifecycle in Demand Planning ERP system. Products within Kenvue may go through transitions in the scenarios like artwork change, formulation changes, case configuration changes etc. The PIPO process helps in aligning the sales history and forecastbetween the predecessors and successors at material code levelunder such scenarios. The purpose of baseline management is to establish a process of generating reliable reproducible baseline forecast which is refreshed every month and is made available in Kenvue planning system for further planning operations. The purpose of sales history management is to ensure the corrected demand history is complete and moved on to the active forecasted version code and/or root code. The process will ensure all qualified cases for soft switch and copy promo are entered into the FC tracker by LDPs. It helps to manage statistical outlier correction and manage corrected demand history in case of SKU delisting by a Customer. 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 Influence machine learning strategy for Digital programs and projects Make solution recommendations that appropriately balance speed to market and analytical soundness Explore design options to assess efficiency and impact, develop approaches to improve robustness and rigor Develop analytical / modelling solutions using a variety of commercial and open-source tools (e.g., Python, PowerBI, Excel) Formulate model-based solutions by combining machine learning algorithms with other techniques such as simulations. Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories. Create algorithms to extract information from large, multiparametric data sets. 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. Develop and embed automated processes for predictive model validation, deployment, and implementation Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment Lead discussions at peer review and use interpersonal skills to positively influence decision making 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 Qualifications Education and Experience: Engineers or Graduate in Science/ Computer Science/ IT related discipline 3-5 years of experience of working in projects, preferably with exposure to data 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 Intermediary skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL) AWS or Azure ML models and time series forecasting Time series Forecasting: ARIMA, S-ARIMA, Linear Reression, Xg Boost, HOlt's Winters, Python/ Cloud (azure or aws or google cloud) Good to Have: FMCG or retail ecosystem Skill Sets: Ability hold discussion with data scientists and understand the logic behind the data Be the custodian on data primarily maintained on excel sheets Ability to pick on market developments and relate to data / business Ability to pick on new concepts and apply to day to day data operations Act as a reliable support to Data Scientist and Business teams Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization & forecasting techniques, and / or deep learning methodologies Proficiency in statistical concepts and ML algorithms Good knowledge of Agile principles and process Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and results Self-motivated and a proactive problem solver who can work independently and in teams

Location: Bangalore, IN

Posted Date: 9/2/2024