Senior Data Scientist

Key Skills

Azure, Data science techniques, Databricks, Deep Learning, Git, Machine learning techniques, MLOps tools, Natural Language Processing (NLP), Neo4J, Presentation skills, Project management, PySpark, Python Programming, Statistical modeling

Job Description

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 vision is to make Unilever data intelligent, partnering with the business to power key decisions with data, advanced analytics and AI to accelerate growth. Our 5 strategies to achieve this are:

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

The Senior 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 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:

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:

• 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
• Design scaled solutions and ensure high quality and timely delivery
• Facilitate industrialization and ongoing operation of solutions through well organised code, clear documentation and collaboration with ML Ops resources
• Govern the work of 3rd party vendors where needed to support delivery, while maximising creation of Unilever IP
• 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
• Possibly lead a team of up to 5 data scientists (WL2B), 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 60-90% 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
• 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 Foundational knowledge
• Optimisation techniques and tools Foundational knowledge
• 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 at least one data science specialism, for example: optimization, simulation, forecasting, natural language processing, computer vision, graph database analytics or geospatial analysis.

General Skills

• Project Management
• Communication / presentation skills
• 3rd party resource management
• CPG Industry analytics

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
• Overall 5-8 years building data science solutions to solve business problems (less experience may be acceptable if balanced by strong post-grad qualifications)
• Experience with open source languages (eg. Python) and preferably with distributed computing (e.g. 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.