Data Scientist

Responsibilities

• Data Pipeline Engineering – Develop automated ELT pipelines in Snowflake.
• Engineer complex SQL transformations using CTEs, subqueries, window functions, and advanced joins.
• Optimize query execution and warehouse organization through appropriate use of tables, views, materialized views, and joins.
• Visualization – create and curate charts and graphics that reveal useful insights.
• Data Wrangling – assemble data from various sources and formats into a single set suitable for analysis.
• Maintain expertise – identify and understand new data sources and analytic innovations that would benefit EVgo and its customers.
• Monitoring & Troubleshooting – identify, manage, and solve technical/engineering problems that you identify using data systems and analytics.
• Industry Knowledge – learn the technical details of the EV charging business and its sources of data.
• Reporting Progress – communicate to others on your progress, obstacles, and learnings.
• Project Selection – propose and promote projects that will answer important questions, support strategic decisions, or optimize control of automated systems.
• Data Exploration – analyze existing data sets to help answer questions and develop hypotheses.
• Communication – document methods and results concisely to present to colleagues.

Qualifications

• Typically requires a Bachelor’s degree in Computer Science or other data science related field, and a minimum of 2 years of related experience; or an advanced degree without experience; or equivalent work experience.
• Full stack data science proficiency including data engineering, web apps, and analytical tools.
• Proven strength in scripting with SQL and Python beyond coursework.
• Applies analytic techniques for data exploration, data visualization, linear regression, categorical models and machine learning.
• Works independently with little oversight, but also knows when to ask for guidance.