
Data Scientist Iii/Sr/Principal
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Overview
Job Description
The Data Scientist role transforms complex business data into actionable insights through advanced analytics and high-quality scripting. Embedded within Business Intelligence (BI), this role emphasizes analytical rigor, clean and scalable code, and enterprise standards to enable data-driven decision-making across EQT.
You'll partner closely with BI Data Engineers and BI Data Analysts across the full analytics lifecycle, from problem definition through implementation and operational use. This role serves as a technical leader for analytics and scripting standards across the organization, with a strong focus on Databricks SQL, Python, and R. While AI and ML may be applied selectively, this position is not centered on building or maintaining enterprise AI models.
The Data Scientist III/Sr./Principal responsibilities include but are not limited to:
- Lead complex analytics initiatives requiring advanced scripting and analytical methods.
- Design, build, and maintain analytical solutions using SQL, Python, and R.
- Contribute across the full analytics lifecycle: discovery, design, development, validation, and refinement.
- Define and enforce enterprise-wide analytics and coding standards, including governance of citizen-developed solutions.
- Conduct code reviews to ensure quality, performance, maintainability, and alignment with standards.
- Develop reusable Python and R packages, shared SQL patterns, and analytical frameworks.
- Support business partners with advanced analytical needs beyond standard BI reporting.
- Apply advanced statistical and analytical techniques to solve complex business problems.
- Selectively apply AI/ML techniques where they deliver clear business value.
- Collaborate with Data Engineers and Architects to ensure alignment with data models, pipelines, and governance.
- Clearly communicate insights, tradeoffs, and recommendations to technical and non-technical stakeholders.
- Stay current with emerging analytics technologies and assess applicability.
Required Experience and Skills:
- Bachelor's Degree in Computer Science, Information Systems Management, Data Science, Information Science, Engineering or another closely related field.
- 6+ years of coding experience.
- Advanced expertise in Python for complex, modular, production-quality scripting.
- Advanced SQL proficiency for implementing and optimizing analytical logic.
- Working proficiency in R for statistical and analytical use cases.
- Proven experience delivering complex analytics solutions in a BI or enterprise environment.
- Strong grounding in software development best practices (version control, testing, documentation).
- Experience defining, enforcing, and reviewing shared or enterprise-wide coding standards.
- Ability to refactor and improve codebases authored by multiple contributors.
- Strong cross-functional collaboration and communication skills.
- Experience mentoring peers and influencing technical direction without direct authority.
Preferred Experience and Skills:
- Working knowledge of Databricks and the Databricks ecosystem, including Lakehouse architecture, PySpark, Databricks SQL, notebooks, workflows/jobs, querying, and Unity Catalog.
- Experience supporting or governing analytics contributions from citizen developers.
- Familiarity with applied statistical learning and advanced analytics techniques.
- Experience collaborating with data engineering and AI/ML teams.
- Exposure to cloud-based analytics platforms and modern data ecosystems.
- Experience developing shared analytics libraries adopted across teams.
- Experience supporting analytics tied to strategic or executive-level decision-making.
- Knowledge of oil and gas operations and related business processes.
- Familiarity with CRM platforms, particularly Salesforce.
Remote work is being considered for this role excluding the following states: California, Connecticut, Delaware, Illinois, Indiana, Louisiana, Massachusetts, Michigan, New Jersey, New York, and Tennessee.
Automate your job search with Sonara.
Submit 10x as many applications with less effort than one manual application.
