Director, Data Analytics

Company Details

 

 

Berkley Oil & Gas, (a W.R. Berkley Company) is an insurance underwriting manager providing unique property and casualty products and risk services to customers engaged in the energy sector.  Our customers recognize the importance of the expertise we provide and appreciate the opportunity to work with professionals who understand their business.  We are in turn committed to delivering innovative products and exceptional service to them, our valued agents and brokers, Berkley Oil & Gas is dedicated in its efforts to be well-informed of the changing dynamics of the industry; support industry efforts to minimize and mitigate risks and hazards in the ‘oil patch’, and to constantly seek ways to improve our products and services to meet customer needs.

 

Company URL: https://berkleyoil-gas.com/

 

The company is an equal opportunity employer.

Responsibilities

The Director, Data Science will focus on leveraging the company’s substantial data assets to deliver actionable business insights using predictive analytics, prescriptive analytics, machine learning, and artificial intelligence. The role will require a high degree of collaboration with the Berkley Oil & Gas Leadership team and cross-functional teams to develop and deploy advanced analytical solutions that generate measurable business value across underwriting, claims, finance, and actuarial practice areas. Responsible for deploying cutting-edge analytical solutions, the Director, Data Science will continuously explore data, data structures, modeling techniques, algorithms, software, programming languages, and testing methodologies to remain current with the state-of-the-art technologies. This role will serve as the lead architect for advanced analytical solutions at Berkley Oil & Gas.   

 

• Provide thought-leadership and direction to company executives regarding how predictive analytics/machine learning/artificial intelligence can lead to value creation and to expand the Berkley Oil & Gas value proposition.
• Identify and capitalize on high-value opportunities to deploy predictive analytics/machine learning/artificial intelligence across the organization.
• Formulate, develop, and experiment with innovative ideas for leveraging internal and external data assets.
• Manage multiple team projects to ensure deliverables meet business requirements and ensure timely completion.
• Translate business requirements, for a given project, into novel technological solutions.  
• Lead team members in the design, development, and implementation of advanced analytics that generate the desired business outcomes.
• Develop and implement methods for the automation of routine data science tasks and machine learning operations.
• Continuously evolve, document, and deploy team standard operating procedures to deliver high quality analytical solutions efficiently and accurately.
• Design and implement CI/CD frameworks and monitoring controls for analytical solutions to guarantee ongoing accuracy, reliability, and compliance with regulatory requirements.
• Act as lead architect in the development of analytical solutions.
• Develops and leads a high performing team focused on building strong analytical, predictive analytics/machine learning/artificial intelligence, research, and business skill sets.
• Actively recruits, coaches, and develops team members.
• Builds a psychologically safe work environment where team members are engaged and can positively contribute to team objectives.

Qualifications

• Possess an intense curiosity and determination to explore and solve complex business problems utilizing data, technology, and analytical techniques.
• Prior leadership experience with increasing levels of responsibility in a Data Scientist role desired.
• Requires 7 to 10 years of experience as a data scientist or in a related field.
• Proven ability to lead advanced analytics projects and deploy predictive models into a production environment.
• Thorough understanding of project management practices and approaches including Agile methodologies.
• Experience with project management software.
• Experience building and deploying deep learning models (e.g., CNN, RNN, LSTM) in a business setting.
• Experience building and deploying natural language processing solutions in a business setting.
• Thorough understanding of best practices for training, testing, validating, and monitoring analytical solutions.
• Advanced understanding of Databases and the SQL language – SQL Server/Oracle/MySQL.
• Experience with multiple programming languages –Python, Java, C++, C#, etc.
• Experience with operating systems including Microsoft Windows and U