Manager - Data Science

Key Skills

Java Programming, Python Programming, SQL, PySpark

Job Description

Senior data scientist will be responsible for the development & deployment of state of art ML algorithms for enterprise level demand forecasting. This position requires development of ML/AI driven technical solution, build, deployment and run of the Forecast Engine Utility (FEU). FEU uses machine learning to produce one volume forecast for CD and SC demand with the target of 80% of volume being no touch. key responsibility, is monitoring, maintaining performance, designing changes and upgrades. Ensuring new builds meet design standards.

The Senior Data Scientist improves business performance in the functional area of Unilever they serve, through the application of world class data science capability. They own planning and delivery of data science on moderate projects or specific modules of a major global initiative.

Key accountabilities:

• Development & Deployment of state of art ML/AI models for timeseries demand forecasting
• Evaluation of FEU market models as per global data science design
• Monitor the performance of FEU demand forecast and intervene with improvement as per the market needs
• 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
• Industrialise and automate model build and run
• Design and lead integration builds and testing
• 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 70-90% 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:

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
• Optimisation techniques and tools Fully Operational
• Python coding Fully Operational
• Data science platform tools e.g. MS Azure, Databricks Fully Operational
• Deep learning (and applications to NLP & Computer Vision) 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 Expert
• Communication / presentation skills Expert
• 3rd party resource management Expert
• CPG Industry analytics Expert

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 8 years (WL2A) 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
• Experience managing the work of team members and 3rd party resource vendors
• Experience presenting insights and influencing decisions of senior non-technical stakeholders

Key interfaces

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