Senior Data Science Software Engineer (Remote)-EG at Verisk
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:
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 have received the Great Place to Work® Certification for the fifth consecutive year. 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. Verisk’s Statement on Racial Equity and Diversity supports our commitment to these values and affecting positive and lasting change in the communities where we live and work.Job Description
As a data scientist in Wood Mackenzie, a Verisk company, you will leverage data scientist and data processing tools to work with our top financial analytics in energy industry both from internal and external clients to provide data insights to them to make important investment recommendations or decisions.
You would have the opportunity to work on the most interesting and challenging data in energy industry. You will be challenged to continue adopting and developing cutting-edge digital technologies on data science, as well as data processing platforms.
You will work with the best in the field of data scientist and growing your skills from working on our team and making significant impact on our business initiatives.
About the role
This role will be part of the data asset team work working as part of a cross functional team to deliver best in class data and analytics to our clients. The mission of this team is to develop the best quality of data through leveraging ML models and AI technologies. It will further help to scale up the operation through applying the innovative technology expanding into getting new data insights for our clients in current and future adjacency domains. You will be working with a very talented team as well as our partners including AWS.
You will be thrilled everyday as being at the very frontline of data science and big data processing technologies. Come to join us if you would like to applying your data scientist skills to solve the challenges and would like to become world class data scientists while learning how to get the best data to help to make energy investment decisions.
The role will can be in places where Verisk had business offices in US or Canada.
The level of appointment to which band on the company banding structure will be dependent on your skills, experience and capabilities demonstrated at assessment prior to offer of employment.Qualifications
- Undergraduate or Graduate degree in computer science, engineering, mathematics or a related quantitative field.
- 3 to 5 years related experience with a Graduate degree, or undergraduate degree with 7+ years related experience.
- End-to-end knowledge of the machine learning project lifecycle including feature engineering, training, validation, and managing models in a production environment.
- Experience with open-source machine learning frameworks (e.g. Scikit-learn, TensorFlow)
- Experience with adopting Spark MLlibs or other popular machine learning packages with Python or Scala to develop ML models for big data
- Experience with ML model management and deployment using tools like MLFlow or similar tools
- Worked with MLOp process to streamline the entire feature engineering, ML modeling and model drift monitoring process.
- Familiar with AWS platform can be leveraged for big data processing for ML modeling such as Glue, SageMaker for big data processing, feature engineering etc.
- Knowledge of deep learning models and reinforcement learning models
- Hands on programming experience for leveraging signal processing to remove noise and identify patterns in data (e.g. Scipy).
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.
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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