At a Glance
- Tasks: Lead the charge in defining and executing ERM's enterprise AI strategy for innovation and efficiency.
- Company: Join ERM, the world's largest advisory firm focused on sustainability and technology.
- Benefits: Enjoy a competitive salary, inclusive culture, and opportunities for professional growth.
- Other info: Be part of a diverse team committed to creating sustainable solutions and driving change.
- Why this job: Shape the future of AI while making a real impact on sustainability and business transformation.
- Qualifications: Proven experience in AI strategy, consulting, and leading multidisciplinary teams.
The predicted salary is between 150000 - 180000 £ per year.
Key Responsibilities
- Define and execute ERM's enterprise AI strategy, driving productivity, service innovation, operational efficiency and new revenue opportunities across the business.
- Shape how ERM adopts, scales and governs AI technologies, while identifying opportunities for automation, tooling, digital transformation and new AI-enabled service offerings.
- Lead the identification, prioritization and delivery of AI and automation initiatives.
- Establish the operating model and governance required for responsible AI adoption.
- Ensure investments deliver measurable commercial and operational value across ERM.
Enterprise AI Adoption & Productivity:
- Own the scaling and adoption of enterprise AI capabilities across ERM, including AI tools, the internal micro-application marketplace, purchased and custom-built enterprise applications, and productivity technologies that automate current-state workflows, improve quality and enhance operating margin.
AI-Led Service Innovation:
- Reimagine ERM's client services using an AI-first mindset, identifying and developing new AI-enabled solutions, products and offerings that create differentiated client value, strengthen competitive positioning and generate new revenue streams.
AI Strategy, Governance & Operating Model:
- Define and lead ERM's AI strategy, operating model and governance framework.
- Ensure technology platforms, data, standards, controls and delivery teams are aligned to support secure, responsible and scalable AI deployment.
Opportunity Pipeline & Investment Management:
- Establish and manage the enterprise AI opportunity pipeline from ideation and prioritisation through business case development, investment decisions, implementation and benefits realization.
- Ensure resources are focused on initiatives with the greatest strategic and commercial impact.
Build vs. Buy vs. Partner Strategy:
- Determine the most effective solution approach for each AI and automation use case.
- Balance internal development, commercial solutions and strategic partnerships to optimise speed, scalability, cost and business value.
Vendor & Partner Ecosystem Leadership:
- Develop and manage ERM's external AI ecosystem, identifying and leveraging strategic technology partners, platforms and service providers to accelerate capability development and value delivery.
Commercialisation & Value Creation:
- Partner with business leaders to influence AI-enabled products, services and pricing strategies.
- Translate AI capability into measurable business growth and market differentiation.
Organisational Mobilisation & Upskilling:
- Lead and coordinate AI delivery teams, including AI Forward Engineers, digital champions and service innovation teams.
- Drive enterprise-wide AI capability building, education and cultural adoption across client-facing and operational teams.
Automation & Technology Transformation:
- Lead discovery and assessment activities across functions to identify high-impact opportunities for automation, AI deployment, workflow optimisation and operating model improvements.
Adoption, Change Management & Value Realisation:
- Drive organisational adoption of AI solutions through structured change management, capability building and stakeholder engagement.
- Establish metrics and reporting to track usage, benefits and return on investment.
Business Case Development & Performance Tracking:
- Quantify efficiency gains, revenue opportunities, quality improvements and risk reduction benefits.
- Provide data-driven recommendations and performance insights to senior leadership.
Influence And Decision-Making Authority:
- Direct activities that have significant impact to the achievement of results for the sub function.
- Focus on the development and implementation of short to mid term strategies (e.g., 3 years or less).
- Negotiate and compromise to influence internal and external parties.
- Communicate with executive leadership regarding matters of strategic importance to the organisation.
- Responsible for improving processes and systems by applying strong conceptual, analytical and interpretive skills.
- Address moderately complex, undefined problems that require detailed analysis and investigation.
- Requires management and leadership knowledge to lead teams across their team.
- Typically has mastery within a specific technical area.
- Directs a team of Managers and/or Managing Consultants.
- Ensures appropriate selection and organisation of talent for the area of responsibility.
Job Requirements & Capabilities Qualifications:
- Significant experience in a senior consulting, transformation, or strategic operations role.
- Strong track record in identifying and delivering technology-led operational improvements in a consulting services environment.
Job Specific Capabilities/Skills:
- Demonstrated experience developing and executing enterprise AI strategies and large-scale digital transformation programmes.
- Strong understanding of AI technologies, machine learning, generative AI, automation platforms and enterprise productivity tooling.
- Experience establishing AI governance, risk management and responsible AI frameworks.
- Proven ability to identify and commercialise AI-enabled products, services and business opportunities.
- Strong financial acumen, including business case development, investment prioritisation and value realisation tracking.
- Experience leading multidisciplinary teams and influencing senior executives on technology and transformation priorities.
- Ability to balance innovation, governance and commercial outcomes within a complex global organisation.
ERM is committed to creating an inclusive workplace where everyone feels valued, respected, and empowered to thrive. We welcome talent from all backgrounds and provide equal opportunities for every candidate. If you have a disability, are neurodivergent, or need accommodations during the selection process, we’re here to support you.
Senior Director of AI employer: Environmental Resources Management (ERM)
At Environmental Resources Management (ERM), we pride ourselves on being an excellent employer, offering a dynamic work culture that fosters collaboration and innovation. Based in the vibrant city of London, our team enjoys competitive benefits, opportunities for professional growth, and the chance to make a meaningful impact in the environmental sector. Join us to be part of a supportive environment where your expertise in data management will be valued and developed.
Contact Details:
Environmental Resources Management (ERM) Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Senior Director of AI
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Environmental Resources Management (ERM)!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Senior Director of AI at Environmental Resources Management (ERM).
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Environmental Resources Management (ERM).
✨Apply Directly through Our Website
When you find a suitable opening like Senior Director of AI at Environmental Resources Management (ERM), make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Senior Director of AI
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Environmental Resources Management (ERM), your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Environmental Resources Management (ERM). Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Environmental Resources Management (ERM)
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Environmental Resources Management (ERM)!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
