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 Data Scientist is responsible for designing, developing, maintaining, and deploying machine learning, simulation, and optimization models. These tasks require a strong data engineering skillset. No data, no model. Bonus points for software engineering skills and knowledge of the functional programming paradigm, since this is a Spark (PySpark) shop.
Beyond technical skills, the position requires communication skills, stakeholder management skills, and the fundamental ability to guide one’s own work and rapidly learn new software.
The position reports to the Director of Business Intelligence and is structured within IT under the Vice President of Applications.
The position is located in Arlington, VA and requires working at the office five days a week.

Responsibilities

• Build end-to-end data science workflows, not just models, that provide quantifiable business value to stakeholders.
• Work the whole data science lifecycle: requirements, data generation, data transformation, model building, model testing, model serving.
• Provide software solutions that are automated and flexible to future business demands. Mercilessly fight technical debt and rework.
• Develop and leverage subject matter expertise in a select portion of the business in order to better design and execute projects.

Qualifications

• Bachelor’s degree in analytical field and 2 years experience or Masters degree in Data Science / similar.
• Expertise in any Python data manipulation library. Ideally, Spark. However, Pandas, Polars, etc are decent starting points.
• Expertise in the basics of data engineering as applicable to preparing data for use by data science models: fact and lookup tables; ingestion; exploration; profiling; cleansing; and transformations such as filter, select, join, groupby, agg, union, when, pivot, melt/unpivot.

Preferred Qualifications

• Ability to write respectable Spark code (PySpark). This means using the Sqark SQL API. Calling SQL code inside Spark or using the Pandas API on Spark does not count.
• Ability to design visualizations in a native Python library such as matplotlib, seaborn, plotly, Bokeh, HoloViz, or Altair.
• Knowledge of software development principles: repositories, source control, data dictionaries / lookup tables, functions, data structures, and unit tests.
• Knowledge of the functional programming paradigm and Spark’s implementation thereof.
• Knowledge of simulation methodologies: system dynamics (SD), agent-based modeling (ABM), and discrete event simulation (DES).
• Knowledge of distributed Python machine learning and deep learning libraries such as SparkML and PyTorch.
• Knowledge of open source Python optimization libraries.

Venture Global LNG is an Equal Opportunity Employer. We do not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status, or any other basis covered by appropriate law.

LI-Onsite

LI-Onsite

• Build end-to-end data science workflows, not just models, that provide quantifiable business value to stakeholders.
• Work the whole data science lifecycle: requirements, data generation, data transformation, model building, model testing, model serving.
• Provide software solutions that are automated and flexible to future business demands. Mercilessly fight technical debt and rework.
• Develop and leverage subject matter expertise in a select portion of the business in order to better design and execute projects