Sustainability Leader - Data Analytics

Tredence Inc.
London
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Climate Data Scientist

Lead Data Scientist

Data Scientist

Freelance Spatial AI and Machine Learning Consulta - Remote

Senior Data Scientist

Senior Data Scientist

About Tredence

Tredence is a global analytics services and solutions company. Our capabilities range from Data Visualization, Data Management to Advanced analytics, Big Data and Machine Learning. Our uniqueness is in bringing the right mix of technology and business analytics to create sustainable white-box solutions that are transitioned to our clients at the end of the engagement. We do this cost effectively using a global execution model leveraging our clients' existing technology and data assets. We also come in with strong IP and pre-built analytics solutions in data mining, business intelligence and Big Data.


Job Summary:


We are seeking an experienced and visionary Sustainability Leader in the Data & Analytics space with 15+ years of experience. The ideal candidate will have a deep understanding of sustainability principles, data-driven decision-making, and a proven track record of leading cross-functional teams. This role will be instrumental in shaping our sustainability strategy by leveraging data analytics to drive sustainable business practices, own sustainability revenue growth and client acquisition.

Key Responsibilities:

  1. Strategic Leadership:
  • Lead the development and execution of sustainability offerings in accordance with market trends across the industries Tredence operates in.
  • Collaborate with sales leadership to create target accounts and lead sales calls with clients.
  • Develop SoWs and staff projects in collaboration with delivery organization to drive revenue growth for sustainability.
  1. People Development:
  • Lead Trainings and mentor people interested in Sustainability to improve their knowledge and hands-on skills.
  • Hire people as required by the business to grow sustainability practice and offerings.
  • Promote diversity, equity, and inclusion within the team and across the organization.
  1. Cross-Functional Collaboration:
  • Partner with various verticals (Retail, CPG, HLS, TMT etc.) and practices (DE, DS, Gen AI etc.) to embed sustainability into their business offerings.
  • Work closely with IT and Studio team to ensure the availability and scalability of sustainability data platforms.
  • Engage with external stakeholders, including customers, investors, and analysts, to communicate sustainability initiatives and performance.
  1. Innovation & Continuous Improvement:
  • Drive innovation in sustainability using emerging technologies, such as IoT, blockchain, and big data.
  • Lead initiatives to improve resource efficiency, reduce carbon footprint, and promote circular economy practices.
  • Identify opportunities for continuous improvement in sustainability practices through data-driven insights.

Qualifications:

  • Experience: 15+ years of experience in data & analytics, with a strong focus on sustainability.
  • Technical Skills:
  • Proficiency in data analytics tools (e.g., Python, R, Tableau, Power BI).
  • Experience with sustainability frameworks and standards (e.g., GRI, SASB, TCFD).
  • Knowledge of AI, machine learning, and big data technologies.
  • Leadership Skills:Proven ability to lead cross-functional teams and manage complex projects.
  • Strategic Thinking:Strong ability to link sustainability goals with business strategy.
  • Communication Skills:Excellent verbal and written communication skills, with the ability to influence and engage stakeholders at all levels.

Key Competencies:

  • Strategic Vision & Leadership
  • Sales Leadership
  • Data-Driven Decision Making
  • Sustainability & ESG Expertise
  • Innovation & Change Management
  • Stakeholder Engagement
  • Collaboration & Teamwork


Why join Tredence?

There is a reason we are one of the fastest growing private companies in the country! You will have the opportunity to work with some of the smartest, friendliest, hardest working people in the data analytics space. You will work with the latest technologies and interface directly with the key decision stakeholders at our clients, some of the largest and most innovative businesses in the world. We offer a 401k match; full medical, dental and vision benefits; a fun, collaborative team atmosphere and a work life balance. Our people are our greatest asset and we value every one of them. Come see why we’re so successful in one of the most competitive and fastest growing industries in the world.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

What Hiring Managers Look for First in AI Job Applications (UK Guide)

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.