Job Title – Senior Manager – Lead Data Scientist

Location – Bangalore

Main Purpose:

The Lead Data Scientist improves business performance in the functional area of Unilever they serve, through the application of world class data science capability. They have end to end ownership for data science on major global initiatives, to include data and modeling approach, technical design, and leadership of team members whether Unilever FTEs or 3rd party employees.

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 VP level

• Highlight recent developments in data science capability which could solve additional challenges, and recommend strategic areas of new capability to develop

• Lead a team of up to 10 Data Scientists and Senior Data Scientists, 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 leading 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 presenting up to exec level, community engagement (e.g. Yammer), publications, blogs, speaking at conferences and participating in industry steering groups.

• Provide ad-hoc & immediate support to the business when needed (for example Covid-19 crisis support)

Depending on the specific project, the Lead Data Scientist can expect 40-60% 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.

Key Skills Required

Professional Skills

• Machine learning Expert

• Statistical modelling Expert

• Forecasting 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 post-doctoral research) 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, Statistics, Engineering, Operations Research); preferably a postgraduate (Masters or Doctorate) degree

• 10 years experience building data science solutions to solve business problems, preferably in the CPG industry (or 7-8 years for those with a PhD)

• Experience with open source languages (eg. Python) and equivalent tools for 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