Data Scientist – FEU Development & QA

JOB TITLE: Data Scientist – FEU Development & QA

LOCATION: UniOps Bangalore

About Unilever

Be part of the world’s most successful, purpose-led business. Work with brands that are well-loved around the world, that improve the lives of our consumers and the communities around us. We promote innovation, big and small, to make our business win and grow; and we believe in business as a force for good. Unleash your curiosity, challenge ideas and disrupt processes; use your energy to make this happen. Our brilliant business leaders and colleagues provide mentorship and inspiration, so you can be at your best. Every day, nine out of ten Indian households use our products to feel good, look good and get more out of life – giving us a unique opportunity to build a brighter future.

Every individual here can bring their purpose to life through their work. Join us and you’ll be surrounded by inspiring leaders and supportive peers. Among them, you’ll channel your purpose, bring fresh ideas to the table, and simply be you. As you work to make a real impact on the business and the world, we’ll work to help you become a better you.

About Uniops

Unilever Operations (UniOps) is the global technology and operations engine of Unilever offering business services, technology, and enterprise solutions. UniOps serves over 190 locations and through a network of specialized service lines and partners delivers insights and innovations, user experiences and end-to-end seamless delivery making Unilever Purpose Led and Future Fit.

Background

For Unilever to remain competitive in the future, the business needs to continue on the path to become data intelligent. The Data & Analytics team will persevere to make Unilever Data Intelligent, powering key decisions with data, insights, advanced analytics and AI. Our ambition is to enable democratization of data, information and insights as a completely agile organization that builds fantastic careers for our people and is accountable for delivering great work that maximizes impact and delivers growth.

This Data & Analytics function endeavours to create clear accountability for all aspects of Data Strategy, Data Management, Information Management, Analytics, and Insights. We are accountable for impact of solutions, maintaining market relevance and minimising unnecessary overlaps in analytics products, ensuring simplicity and that our solutions better meet the needs of our users. We partner with the Digital and Data Legal Counsel to ensure that our Data Defence (Privacy, Governance, Quality, etc) is well structured and sufficiently robust to use data and AI correctly throughout the enterprise. We democratize information across the business, while supporting the culture shift required for data driven decision making.

Our 5 Strategies To Achieve This Are

Our vision is to make Unilever data intelligent, partnering with the business to power key decisions with data, advanced analytics and AI to accelerate growth.

Accelerate & simplify access to relevant data, information and insights Build in-house, leading-edge data, information, insights & analytics capability Lead the data & insights culture and careers to empower employees across Unilever Rapidly embed analytics products, solutions and services to drive growth Advance Information Automation at Scale

The Data Scientist is an exciting role in the Data Science Centre of Excellence (CoE) team within D&A. This team builds state of the art machine learning algorithms, maximising the impact of D&A’s solutions in driving enterprise performance. Typical initiatives include building a state of art enterprise scale demand forecasting engine, optimizing trade promotion investments, accurately forecasting customer demand, using NLP to glean insight on consumer trends from search data, and making individual assortment recommendations for each of the millions of stores that sell Unilever products. The role will work closely with a D&A functional team such as Customer Development or Supply Chain along with business stakeholders, addressing both large transformation programs and near-term business problems.

Main Purpose Of The Job

(A concise statement setting out the main purpose and objectives of the job)

Forecast engine utility (FEU) is the Unilever’s inhouse AI/ML based demand & promotion forecasting solution. Data Scientist role will be responsible for regional development of this technology and own the forecast KPIs for the respective region (group of countries). Key Responsibility of this role will be to a data science design authority during the global forecasting solution rollout for the region.

Key Responsibility

• Develop and Govern data science build process and model Change landscape for enterprise level one-forest solution together with business team such as digital supply chain, integrated customer development team and Build partners
• Technical due diligence of market DS work. Advanced knowledge on building and implanting scalable forecasting solution
• Perform FEU forecast model diagnosis during development phase
• Track model features and periodically evaluate model performance KPIs
• Identify key gaps early on in development on data, feature or model which may lead to poor performance in parallel run
• Push global DS model guideline/governance during project phase
• Identify and proposed continuous improvement plan from FEU re-usable module (FEU LEGO)
• Training and supervising build team on global forecasting library (LEU-LEGO) and strengthening technical gaps in global library by customizing the same as per region specific data and model requirements.
• Write efficient and well-organized ML based software to ship products in an iterative, continual-release environment.
• Engaging in strategic discussions to identify problems while measuring and improving the quality of workflows. Identify and implement opportunities to improve tooling and implementation of scalable solutions
• Working in an agile environment with globally distributed teams.
  

To do this job successfully, you will need strong skills in Timeseries models, Machine Learning, and strong hold of object-oriented programming with large data. Experience in enterprise level ML product development is required.

Key Accountabilities

(Describe the decisions this role is accountable for and the responsibilities/deliverables expected)

• Development & Deployment of state of art ML/AI models for timeseries demand forecasting
• Evaluation of FEU market models as per global data science design
• Provide new solutions to enhance the FEU demand forecast for new products, baseline, promotion lift and total forecast
• Lead pilots and experiments to improve forecasting performance and scope
• Implementation of scalable data science solution with market explainability features
• Manage forecast run performance to achieve forecast accuracy, bias and no touch adoption targets
• Responsible for technical strengthening of market data science models
• Interact with relevant teams to identify business challenges where data science can help
• Apply comprehensive data science knowledge to propose optimal techniques for key business challenges
• Create detailed data science proposals and project plans, flagging any limitations of proposed solution
• Design and prototype experimental solutions, particularly machine learning models
• Facilitate industrialization and ongoing operation of solutions through well organised code, clear documentation and collaboration with ML Ops resources
• Represent Data Science in cross-functional governance of projects, engaging with stakeholders up to Director level
• Highlight recent developments in data science capability which could solve additional challenges
• Lead a team of up to 1-2 data scientists / interns (WL2A), providing career mentorship and line management
• Provide technical guidance to data scientists across D&A, particularly on the projects you lead
• Support the growth of D&A’s data science capability by contributing to activities such as tool and vendor selection, best practice definition, recruitment, and creation of training materials
• Build the reputation of D&A’s data science capability within Unilever and externally, through activities such as community engagement (e.g. Yammer), publications or blogs
• Provide ad-hoc & immediate support to the business when needed (for example Covid-19 crisis support)
  

Depending on the specific project, the Senior Data Scientist can expect 80-90% of their work to be hands-on prototyping solutions, with the remainder spent planning and designing, overseeing and reviewing work of project staff, interfacing with stakeholders and managing team members.

Experience And Qualifications Required

(Detail essential and desirable experience)

Standards Of Leadership Required In This Role

• Personal Mastery (Data-science and advanced analytics)
• Agility
• Business acumen
• Passion for High Performance
  

Key Skills Required

Professional Skills

• Machine learning Expert
• Statistical modelling Expert
• Forecasting Expert
• Explainable ML/AI Expert
• Python/Pyspark coding Expert
• Data science platform tools e.g. MS Azure, Databricks Fully Operational
• Deep learning (temporal & spatial learning ) Fully Operational
• Collaborative development using Git repos Fully Operational
• Automated Machine Learning platforms Foundational knowledge
  

While a broad data science technical background is required, the role will benefit from deeper skills (for example graduate studies or prior work experience) in one of the following areas, optimization, simulation, forecasting, natural language processing, computer vision or geospatial analysis.

General Skills

• Project Management Operational
• Communication / presentation skills Expert
• 3rd party resource management Operational
• CPG Industry analytics Foundational knowledge
  

Strong communication and stakeholder engagement skills are essential, including the ability to influence peers and senior business stakeholders across Unilever.

Relevant Experience

• Minimum of B.S. in a relevant technical field (e.g. Computer Science, Engineering, Statistics, Operations Research); preferably a postgraduate (Masters or Doctorate) degree
• At least 3 years (WL1 D) building data science solutions to solve business problems, preferably in the CPG industry (less experience may be acceptable if balanced by strong post-grad qualifications)
• Experience with open source languages (eg. Python) and preferably with distributed computing (PySpark)
• Experience deploying solutions in a modern cloud-based architecture
  

Key Interfaces

(List any external and internal contacts arising from the job)

Internal

• Unilever operational, marketing, customer development, supply chain, product & finance teams
• Internal D&A teams (Engagement teams; Data CoE; Solution Factory; BDL Factory; Information Factory; Tech Transformation)
• Wider Unilever analytics and data science professionals
  

External

• 3rd party Data Science vendors
• Universities
• Industry bodies