Sustainability Analytics Lead at Olam Nigeria Limited

Unit Overview

• The global climate crisis requires us to reduce global GHG to net-zero emissions by 2050 in line with the Paris 1.5 agreement; to do so whilst feeding 10 Billion people sustainably and ensuring inclusive growth, is the greatest challenge of our lifetime.
• Leading the Susatinability Analytics Unit, you will work in close collaboration with the Environmental, Social & Goverance pillars and will provide support in terms of data collection, collation, analysis & presentation.
• You will be positively contributing and supporting with data analytics to the initiatives for regenerative agriulture, ecosystem conservation, environmental footprinting, and better livelihoods for farmers by generating insights that drive positive action.

The core roles of the Sustainability Analytics Unit in the Sustainability department are:

• Data collection, sharing and visualization
• Benchmarking and alignment of metrics and data collected and
• Policy and audit framework updates, monitoring and follow-up.

Others:

• The Sustainability Analytics Unit ensures that we collect and monitor the right data to identify risks, monitor activities, and measure impact.
• The team ensures that we have the right systems and tools to collect, share and visualize data -- generating insights that enable sustainability and business teams to identify risk hotspots, measure progress and communicate value.
• The team benchmarks and aligns metrics with global standards and best practices, as well as relevant departments such as AtSource and Internal Audit.
• They ensure that sustainability policies and checklists are up-to-date, and that non-compliances are flagged and followed-up.
• The team supports Social & Natural Capital colleagues to design and analyze surveys and conduct research as required.

Role Overview

• The Sustainability Analytics Lead has overall responsibility to establish best practices in modeling methodology, target setting, data collection, analysis, and reporting for both environmental & social sustainability programs.
• He/She will be monitoring risks, measuring impact, and generating insights that support the achievement of Olam’s aims for climate-positive, nature-positive and livelihoods-positive supply chains and operations.

Responsibilities
The Sustainability Analytics Lead is responsible to:

• Lead the development of ESG metrics, methodologies and tools for generating insights and measuring outputs and impacts, in line with best practices and the requirements of stakeholders such as business and sustainabiltiy colleagues, investors, donors, certifying bodies, communications and sustainability accounting functions.
• Apply AI and other quantitative methods & must also demonstrate strong quantitative skills, including AI and Machine learning methods
• Support the ESG pillar leads’ needs in research, data analysis, AI solutions, and mathematical/statistical modeling.
• Build, validate and update complex data models
• Monitor social and environmental risks in farms and supply chains, harnessing a variety of sources and tools including publicly available data, GIS maps, and field-levels surveys and processes. Ensure that risks are systematically flagged to the relevant teams.
• In collaboration with sustainability and digital colleagues, coordinate the development of digital solutions and applications (e.g. for farmer surveys, farmer service delivery, ESG reporting, and risk monitoring. Identify opportunities to automate data collection and management
• Stay abreast of trends and best practices in data mining and analytics, impact metrics and GIS, especially with applications for sustainable agriculture, monitoring land use change, and assessing social impact.

Qualifications

• Master's or Ph.D. Degree in Data Analytics, Statistics, GIS Systems, Environmental Anaytics, Physics, Mathematics, Statistics, Data Science (preferred including Machine Learning), or equivalent quantitative research experience if she/he has a different academic background
• 10 - 15 years of relevant professional experience
• A personal passion for sustainable agriculture and food systems
• Experience managing data science and quantitative analysis within a data-intensive environment. (e.g., energy, tech, finance desirable)
• Demonstrated ability to work with large volumes of data
• Excellent understanding and ongoing learning of Data Science and Machine Learning frameworks, tools, and algorithms, both for regression and classification problems (e.g., Python, ArcGIS, Java, MatLab are highly desirable)
• Understanding of Sustainability reporting standards like GRI, SASB, PRI etc are desirable
• Strong leadership and interpersonal skills, with a proactive, solution-oriented and innovative mindset
• Critical thinking skills, organisational skills, and the ability to design and manage programmes.
• On-the-ground experience and a good understanding of agri-business models and success factors are highly desireable
• Willing to occasionally travel to remote operational areas
• French or other languages are an asset