Senior Data Scientist

About the position

Venture Global LNG (“Venture Global”) is a long-term, low-cost provider of American-produced liquefied natural gas. The company’s Louisiana-based export projects service the global demand for North American natural gas and support the long-term development of clean and reliable North American energy supplies. Using reliable, proven technology in an innovative plant design configuration, Venture Global’s modular, mid-scale plant design will replace traditional designs as it allows for the same efficiency and operational reliability at significantly lower capital cost. The Senior Data Scientist is responsible for developing and maintaining data analytics solutions and machine learning algorithms. As a senior role, the expectations are to mentor junior data scientists, further develop the data science lifecycle and best practices, and contribute to strategic discussions. The measures of an ideal candidate include communication skills, technical proficiency, collaboration, mentorship, strategic-thinking, and willingness to learn new things. This new position will be based in our Arlington, VA headquarters and report to the Director of Business Intelligence. This position is structured within IT under the Vice President of Applications.

Responsibilities

• Develop solutions to business problems using the data science life cycle.
• Develop and maintain data analytics solutions and machine learning algorithms.
• Develop comprehensive project plans for implementing data science projects including solution architectures, resourcing, and dependencies.
• Use predictive modeling and classification techniques to improve LNG production efficiency and mitigate safety or downtime risks.
• Mine and analyze data from a data lake or data warehouse to drive optimization.
• Work with stakeholders to identify opportunities to leverage data science to drive business solutions.
• Understand where key decisions are needed and communicate options for solving business problems with stakeholders.
• Provide ETL requirements to data engineers to effectively curate files for data analytics.
• Document data science algorithms for maintainability.
• Work with IT leadership to further define the data science life cycle and enhance the data science technology stack and architecture.
• Design data architecture for future platform growth including data warehousing, machine learning, streaming analytics, and data visualization.
• Assist in testing, governance, data quality, training, and documentation efforts.
• Mentor junior data scientists and data analysts.
• Actively engage in business stakeholder requirement workshops to understand, interpret, and translate requirements into effective technical solutions.

Requirements

• 5+ Years of practical data science/data analytics experience.
• Bachelor’s degree in Computer Science, Data Analytics, Engineering, Mathematics, Business, or related field of study.
• Knowledge in cloud data analytics solutions, managing, developing, and maintaining machine learning solutions.
• Fundamental skills in data processing languages such as SQL, Python, or Scala.
• Knowledge in building data science solutions using cloud data services.
• Ability to self-manage and make your own decisions.
• Strong presentation skills to effectively communicate results of analytics to stakeholders.
• Strong documentation skills.
• Excellent interpersonal and communications skills, with strong critical thinking and attention to detail.
• Strong work ethic with ability to effectively prioritize, meet deadlines, adapt to changing priorities and business needs, and succeed in a fast-paced environment.
• Excellent attention to detail and the ability to efficiently summarize and prioritize information.

Nice-to-haves

• Experience with Azure infrastructure especially Azure Data Lake and Azure Data Factory.
• Experience using Databricks for machine learning algorithm development.
• Experience in coding languages primarily PySpark, Python, and SQL.
• Experience in agile development and sprint planning.
• Experience utilizing DevOps.
• Experience working with streaming datasets/IoT.
• Strong technical writing skills.