Wood Mackenzie is the global leader in data, analysis and consulting across the energy, chemicals, metals, mining, power and renewables sectors.  

Founded in 1973, our success has always been underpinned by the simple principle of providing trusted research and advice that makes a difference to our customers. Today we have over 2,000 customers ranging from the largest global energy companies and financial institutions to governments as well as smaller market specialists.  

Our teams are located around the world. This enables us to stay closely connected with customers and the markets and sectors we cover. Collectively this allows us to offer a compelling combination of global commodity analysis with detailed local market knowledge.  

We are committed to supporting our people to grow and thrive. We value different perspectives and aspire to create an inclusive environment that encourages diversity and fosters a sense of belonging. We are committed to creating a workplace that works for you and encourage everyone to get involved in our Wellness, Diversity and Inclusion, and Community Engagement initiatives. We actively support flexible working and are happy to consider alternative work patterns, taking into account your needs and the needs of the team or division that you are looking to join.   

Hear what our team has to say about working with us:  

https://www.woodmac.com/careers/our-people/ 

We are proud to be a part of the Verisk family of companies!  

At the heart of what we do is help clients manage risk. Verisk (Nasdaq: VRSK) provides data and insights to our customers in insurance, energy and the financial services markets so they can make faster and more informed decisions.    

Our global team uses AI, machine learning, automation, and other emerging technologies to collect and analyze billions of records. We provide advanced decision-support to prevent credit, lending, and cyber risks. In addition, we monitor and advise companies on complex global matters such as climate change, catastrophes, and geopolitical issues.   

But why we do our work is what sets us apart. It stems from a commitment to making the world better, safer and stronger.   

It’s the reason Verisk is part of the UN Global Compact sustainability initiative. It’s why we made a commitment to balancing 100 percent of our carbon emissions. It’s the aim of our “returnship” program for experienced professionals rejoining the workforce after time away. And, it’s what drives our annual Innovation Day, where we identify our next first-to-market innovations to solve our customers’ problems.    

At its core, Verisk uses data to minimize risk and maximize value. But far bigger, is why we do what we do.  

At Verisk you can build an exciting career with meaningful work; create positive and lasting impact on business; and find the support, coaching, and training you need to advance your career.  We’ve been recognized by Forbes as a World’s Best Employer and a Best Employer for Women, testaments to our culture of engagement and the value we place on an inclusive and diverse workforce.  

Do you have a passion for data? Are you a problem-solver with the ability to quickly understand complex processes? Do you continually seek and find meaningful patterns in data? Then this role could be for you. We are looking for a Data Scientist - someone with a data focus, mathematical mindset, and collaborative project experience. This role will be key to delivering advanced analytics projects within both new and existing business workflows, working alongside expert data professionals and business unit SMEs to deliver new insight and analytics to our clients. The candidate should be able to commute to one of our offices in Either Edinburgh or London.

About the role
This role will form part of the Innovation and Analytics Lab and will work closely with a variety of other functions and teams throughout Wood Mackenzie. The successful candidate will spend the majority of their time performing data exploration/visualization and developing machine learning models. The success of this role will require collaborative development & problem-solving. Our team has consciously developed a supportive and inclusive culture, guided by five principles:
•    Fixate on Business Outcome
•    Sustain an Innovation Mindset
•    Cultivate Constructive Discord
•    Encourage Curiosity and a Growth Mindset
•    Maintain Collaborative Habits

Key Responsibilities
•    Develop and/or use various algorithms to build predictive models within a variety of business domains.
•    Collaborate with business units to understand their problems and goals, specify hypotheses, and identify appropriate modeling approaches / statistical tests.
•    Collaboratively perform analyses of structured and unstructured data to solve multiple complex business problems using advanced statistical techniques and mathematical analyses.
•    Use strong knowledge in algorithms and predictive models to investigate problems, detect patterns, and recommend solutions.
•    Use strong programming & data engineering skills to explore, examine, prepare, and interpret large volumes of data in various forms.
•    Design, prototype, and productize data sets that are used for advanced analytics.
•    Read and ingest academic-oriented literature, and collaborate with subject matter experts to build better predictive models.

Knowledge and Experience
Required Data Science / Machine Learning stack:
•    Languages / packages: Python, SQL, pandas, NumPy, scikit-learn, PyTorch / TensorFlow / Keras, Plotly / Matplotlib, Jupyter
•    Algorithms: Classification, Regression, Clustering, Neural Networks, Time Series, Ensemble Models, Feature Selection & Extraction, Mathematical Optimization
•    Visualization: Spotfire / Power BI / Tableau / similar
•    Version control: Git

We are looking for someone with:
•    advanced degree in statistics, computer science, applied mathematics, or a related field
•    strong knowledge of advanced applied data science: mathematical, computational, statistical modeling techniques, neural networks, data analysis and visualization
•    professional experience as a data scientist or machine learning engineer
•    professional experience working with big data and relational databases
•    extensive experience with data manipulation, analysis, and visualization
•    hands-on modeling experience building machine learning models
•    familiarity with collaborative development using the agile-like methodology

Nice-to-have:
•    cluster computing with Apache Spark
•    orchestration tools such as Apache Airflow
•    non-relational databases such as MongoDB, Apache Cassandra, etc.
•    network graph analysis & graph databases such as Neo4j
•    DevOps – CI/CD
•    cloud computing environments – AWS / GCP / Azure / etc.

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Verisk Analytics is an equal opportunity employer. 

All members of the Verisk Analytics family of companies are equal opportunity employers. We consider all qualified applicants for employment without regard to race, religion, color, national origin, citizenship, sex, gender identity and/or expression, sexual orientation, veteran's status, age or disability. 

http://www.verisk.com/careers.html 

Unsolicited resumes sent to Verisk, including unsolicited resumes sent to a Verisk business mailing address, fax machine or email address, or directly to Verisk employees, will be considered Verisk property. Verisk will NOT pay a fee for any placement resulting from the receipt of an unsolicited resume. 

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