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You will be updated with latest job alerts via emailWood Mackenzie is the global data and analytics business for the renewables energy and natural resources industries. Enhanced by technology. Enriched by human intelligence. In an everchanging world companies and governments need reliable and actionable insight to lead the transition to a sustainable future. Thats why we cover the entire supply chain with unparalleled breadth and depth backed by over 50 years experience. Our team of over 2400 experts operating across 30 global locations are enabling customers decisions through realtime analytics consultancy events and thought leadership. Together we deliver the insight they need to separate risk from opportunity and make confident decisions when it matters most.
Wood Mackenzie Values
Do you have a data science background and experience of working on traditional AI projects If so wed love to hear from you.
Wood Mackenzie is an industryleading data analytics company that provides analysis and insight on the worlds natural resources with a presence all around the globe. Were working on a next generation data analysis & visualisation platform that enables our customers to drive billiondollar decisions and accelerate the worlds transition to a more sustainable tomorrow. Were looking for a Data Scientist to join our team.
Role Purpose
This role will be working within our AI group and focus on the research development and delivery of Generative AI solutions within our products. Youll collaborate closely with a crossfunctional team of data scientists software engineers data engineers and product managers that deliver our product roadmap. Youll apply advanced AI techniques and ensure high standards of data quality and integrity in our solutions.
The successful candidate for this role must have a strong Data Science background and understand the challenges of delivering data products with a commitment to incremental delivery. Proven experience of data science projects and the ability to articulate ideas effectively across multiple business areas is essential.
Main Responsibilities:
Work on the design development and evaluation of AI and Machine Learning models with a focus on Generative AI and datadriven product features
Collaborate with product engineering and domain teams to understand user needs and develop innovative productionready AI solutions aligned to strategic objectives
Support the delivery of analytical components from concept to deployment working closely with other team members to validate approaches and ensure quality outcomes
Apply Machine Learning / AI and advanced modelling techniques leveraging appropriate data engineering and statistical concepts
Write maintainable testable and optimised code and contribute to the continuous improvement of our data science practices
Participate in peer reviews knowledge sharing sessions and technical discussions while continuously developing your own skills and knowledge and receiving mentorship from senior colleagues
About You
Essential
You have applied Generative AI or Machine Learning techniques in realworld projects to develop and deliver innovative products
You likely have a degree in a technical or quantitative field (e.g. computer science engineering mathematics physics or similar) and some professional experience applying data science in a commercial or research setting.
You communicate clearly with both technical and nontechnical stakeholders and enjoy working collaboratively in a crossfunctional environment
You are familiar with version control agile practices and collaborative coding environments
Desirable
You demonstrate curiosity a willingness to learn and an interest in growing your expertise within data science and AI
You have strong analytical skills are detailoriented and enjoy turning data into actionable insights.
You are enthusiastic about learning new technologies improving your skills and contributing to meaningful business outcomes.
You enjoy working in a collaborative team environment and take ownership of your work.
Our Tech Stack
We use a wide variety of tools and technologies across our products. For this role were looking for:
Familiarity with Generative AI and experience with technologies such as LLMs RAG Vectorstores and LangChain; including LLMs such as those from Anthropic OpenAI and Meta
Strong Python skills and experience with Jupyter Notebooks and libraries such as pandas NumPy scikitlearn
Understanding of core ML tasks including classification regression clustering and time series forecasting
Experience with SQL and an understanding of data modelling and querying across structured and semistructured data
Exposure to cloud platforms such as AWS (e.g. SageMaker Bedrock) and interest in learning MLOps tools and practices
Experience using version control systems such as Git and GitHub
Other Technologies You Might Encounter
Our services are deployed to AWS typically using Bedrock Lambda ECS with CloudFormation and CDK for infrastructure configuration
Our web products are developed using TypeScript React and Redux
We implement GraphQL and RESTful APIs using NodeJS and Python
Our backend services are implemented in C# / .NET or Typescript / NodeJS
DynamoDB Redshift Postgres Elasticsearch and S3 are our go to data stores
We run our ETL data pipelines using Python
Equal Opportunities
We are an equal opportunities employer. This means we are committed to recruiting the best people regardless of their race colour religion age sex national origin disability or protected veteran status. You can find out more about your rights under the law at
If you are applying for a role and have a physical or mental disability we will support you with your application or through the hiring process.
Equal Opportunities
We are an equal opportunities employer. This means we are committed to recruiting the best people regardless of their race colour religion age sex national origin disability or protected veteran status. You can find out more about your rights under the law at
If you are applying for a role and have a physical or mental disability we will support you with your application or through the hiring process.
Full-Time