Key responsibilities :
Deliver commercial value through data, analytics, and AI projects / initiativesCollaborate with key stakeholders to design and lead high-impact projects / initiatives, with SMART business objectivesEnsure impact by tracking and delivering commercial value, measured in revenue / EBIT growth, cost savings, and uplift / improvement compared to previous approachesLead projects end-to-end, from ideation through technical execution to business implementation and automationPartner with the global team and counterparts to drive faster speed to execution;
promote re-use; borrow shamelessly and share selflessly across regionsBuild consensus around buy or build decisions when necessary.
When buying, partner with colleagues to assess capability of external AI vendors.
Based on priorities set by stakeholder needs, set and own the local data strategy to optimize value and useIdentify relevant internal and external data sources to understand behaviors, attitudes, preferences, and trendsWork with data stewards and data owners to implement formal measurements of data quality and usability, and a plan to improve over timeEncourage the use of data and data-driven decision makingEmpower colleagues with self-service capabilities where possible / practical through data tools and dashboards
Manage local implementation and automation of projects, embedding analytics within the organizationOversee project lifecycle management : quickly scale in-progress to pilot;
pilot to production; production to automation, freeing up resources to work through backlogsIntegrate analytical / AI solutions into systems and processes, automating completed workEffectively manage risks, issues, and dependencies;
use personal network and stakeholder relationships to resolve roadblocksPromote agile working / practices within the broader team
Grow and develop team, and AI and analytical acumen throughout the organizationBuild a world-class team of data scientists and engineers;
mentor team, both in terms of daily troubleshooting and long-term career development; over time, build a reputation for LS&Co.
as an employer of choice for data and AI professionalsEffectively manage team and budget, for the right blend of internal and external resourcesBuild a community of data and analytics-savvy colleagues through a combination of training, knowledge sharing and inspiration / best practice sharing
Demonstrate a spirit of cooperation, teamwork, and transparencyBe a great team player, demonstrating empathy and positive psychology, and with strong cross-functional working relationships across commercial and technology teams, locally and globallyLead by example and provide ongoing mentorship and guidance to the teamPromote a growth mindset and culture of continuous learning and improvement, empathy, humility and positive psychologyEnsure accuracy and relevance of all work through peer reviews, pair-programming, and close partnership with colleagues across the businessDrive transparency with all code and project plans saved to global Confluence / Git repositories;
actively promote re-use
Team management : Responsible for initial team of two data scientists (medium to high professional level), likely to grow to approximately four data scientists, two data engineers, and one implementation lead within one year.
Budget ownership : Oversee and make effective use of annual budget to fund external resources, data and technology enablement.
Reporting line : Solid line to Global Commercial Head of Data, Analytics, and AI