Lead Data Scientist

Key Skills

Agile methodologies, Algorithms, Apache Hadoop, Apache Hive, Azure, Data science techniques, Databricks, Deep Learning, Git, Machine learning techniques, Marketing analytics, MLOps tools, Natural Language Processing (NLP), Neo4J, Optimization, Presentation skills, Project management, PySpark, Python Programming, SAP, Statistical modeling

Job Description

Role Context:

We are looking to hire a Senior Data Science Lead, for South Asia to join the in market Data & Analytics team.

This is an exciting role in the Data & Analytics team partnering the 2nd largest Unilever business HUL. Unlocking growth, consumer and customer value while driving efficiencies and building future ready capabilities using business analytics, ML & AI is core to what we do everyday!

Your Team: The Data & Analytics In-Market team helps our Unilever businesses win competitively in market using data, data science, and analytics. We leverage Our close engagement/ relationship with brands, marketing, supply chain and customer development leadership with a (highly technical) data science team to solve for both large transformation programs and near-term business problems. The team is composed of business analysts, data scientists, and data experts who can: quickly understand the business context + problem, apply advanced mathematics and/or statistics to large data sets; and operate in cloud based environments where data, models, and user interfaces reside in the same platforms-core technologies

What You’ll Lead In This Role

• Design the data science strategy and roadmap for HUL and South Asia with the Head of Data & Analytics in-market
• Specifically, this role will focus on working on real business problems coming from Customer Development, Supply Chain, and eCommerce.
• Gather, analyse, and model data to solve complex business problems and evaluate scenarios to make predictions on potential future outcomes and support decision making.
• Partner and engage with business & transformation leads and teams to identify, evolve and fully understand the key business questions and how to deliver relevant insights that lead to actions. Set up the MLOPs framework for the market in collaboration with the global team
• Lead and mentor the junior data science team members reporting to you
• Bring out the “art-of-possible” in data science from outside the organization by connecting with the start-up ecosystem, industry leaders and academia
• Partner with the Global Unilever Data Science leadership on learning and product deployment in-market
• Develop and manage key Partnerships with strategic and niche analytics service providers and delivery partners

Key Accountabilities

• Build and deliver the joint business plan priorities between Data & Analytics team and the market leadership teams.
• Build data-science and algorithmic solutions to address business problems requiring descriptive, diagnostic, predictive, and / or prescriptive analytics
• Drive new value from insights from connecting external and internal data sources
• Innovate new data and analytic methodologies driven by local needs which feed into global productpipeline
• E2E accountability of quality of recommendations, insights and data science solutions developed and deployed in market
• Budget and project management for Data Science initiatives
• There will be 2- 5 Unilever employees reporting directly/indirectly into this role, and between 3-10 third party contractors this role is accountable for.

Relevant Experience

• B.S. or M.S. in a relevant technical field (Operations Research, Computer Science, Statistics, Business Analytics, Econometrics, or Mathematics). Overall experience of 8+ years preferred
• Experience in setting up and/or managing an organization wide data science team is a must (3-4years).
• Strong track record in solving analytical problems using quantitative and statistical approaches
• Expert knowledge in one or more of the following: marketing analytics, recommendation engines, forecasting, and investment optimization.
• A sound understanding of fundamental data science techniques like XGBoost, LGB, LSTMs, and optimization techniques like Genetic Algorithms.
• Experience in designing end to end architectures on Azure and building scalable solutions using MLOps.
• Ability to manipulate and analyse complex, high-volume, high-dimensionality data from varying sources (Nielsen, SAP, Retailer ePOS; both structured and non-structured data)
• Experienced knowledge working with large data sets, experience working with distributed computing tools a plus (Map/Reduce, Hadoop, Hive)
• Passion for empirical research and for answering hard questions with data
• Ability to apply an agile analytic approach that allows for results at varying levels of precision
• Ability to communicate complex quantitative insights in a precise, and actionable manner to business stakeholders.

Data & Analytics In Unilever

For Unilever to remain competitive in the future, the business needs to continue its path to become data intelligent. The Information and Analytics team is responsible for building data, data science and analytics as a core capability to help the business become data intelligent and drive business and organization performance. The team will deliver advanced products at scale and work closely with the market teams to ensure that decisions in Unilever are augmented with insight & recommendations wherever possible.

There are five major themes to the Information and Analytics strategy:

• Deliver Intelligent systems at scale. Powering Business (cross functional), Customer Development area & Supply Chain through data and analytics. Building out the right applications to enable business teams to move faster, with more accurate and future looking decisions leveraging Big Data & Data Science
• Winning disproportionately in Markets. We believe that the best way to move the needle for Unilever in Analytics is to work with leading geographies to create analytics products that make a significant impact on our business
• Drive Unilever to assisted and predictive decision-making. The future is about assisted decision-making with machines (AI/Cognitive Computing/Machine Learning) unlocking the insights from vast deluge of consumer, customer & internal data, and presenting this in a way that is simple for our teams.
• Make data a true asset. Better data and data science access for every part of Unilever, across the 3
• -data framework (Connectivity, Growth, Continuous Improvement) and leading through the Enterprise Data Executive.
• World-class Information: One Version of the Facts. Continued excellence in delivery of diagnostics and insights to focus attention when and where it matters with a focus on Big Bets, Strategic Initiatives and Leadership team reporting.