Data Scientist

Venture Global LNG
Arlington, TX, United States
6 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
5 years minimum
Compensation
$180,000.0 - $230,000.0
Working hours
Regular working hours

Tech stack

Agile Methodology Business Analytics Applications Data Analysis Microsoft Azure Cloud Computing Cloud Database Databases Data Architecture Data Files Extract Transform Load (ETL) Data Visualization Data Warehousing
+20 more
DevOps Document-Oriented Databases IT Management Python (Programming Language) Machine Learning Scrum Methodology Azure Data Lake Requirements Management SQL Databases Data Streaming Data Processing Scripting Azure Data Factory Data Lakes Pyspark Information Technology Data Analytics Service Stack Databricks Programming Languages

Job description

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.

The position will be located in Arlington, VA.

General Description Duties & 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 documentations 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.

Preferred Experience

  • 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., Agile Programming Methodologies, Algorithms, Architectural Design, Best Practices, Biology, Business Development, Business Intelligence, Business Solutions, Cloud Computing, Communication Skills, Computer Science, Cost Control, Data Analysis, Data Lake, Data Processing, Data Science, Data Sets, Data Visualization, Data Warehousing, Database Extract Transform and Load (ETL), Detail Oriented, DevOps, Equipment Maintenance/Repair, Establish Priorities, Internet of Things, Interpersonal Skills, Liquified Natural Gas (LNG), Machine Learning, Mathematics, Mentoring, Microsoft Windows Azure, Natural Gas, Oil and Gas, Plant Layout and Design, Predictive Modeling, Presentation/Verbal Skills, Problem Solving Skills, Process Improvement, Project Development, Project Planning, Python Programming/Scripting Language, Requirements Management, SQL (Structured Query Language), Scala Programming Language, Scientific Publications, Sprint Planning, Technical Leadership, Technical Writing, Time Management, Writing Skills

About the company

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.

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