Data Scientist

Context Labs seeks an early-career Data Scientist to support deployment of its decarbonization platform. The role develops and validates analytical methods for energy and emissions data, turning research and customer-specific calculations into scalable product capabilities.

What you'll do:

• Work with domain experts to understand engineering and emissions methodologies, assumptions, and requirements and translate them into computational solutions
• Develop, implement, validate, and document robust and reproducible emissions calculations and analytical methodologies
• Explore complex customer datasets, understand their structure and meaning, identify data-quality issues, and investigate discrepancies
• Implement scalable analytical workflows using Python, SQL, and PySpark, working with data engineers to move solutions into repeatable production workflows
• Help generalize customer-specific calculations, research ideas, and analytical prototypes into reusable software and product capabilities
• Apply statistical methods to validate results, quantify uncertainty, and understand the limitations of available data and methodologies
• Work within an ontology- and knowledge-graph-based framework to connect data to the entities, relationships, and concepts they represent
• Write maintainable, modular Python code and contribute through Git, code review, testing, and documentation
• Apply machine learning methods, including regression, classification, time-series analysis, and anomaly detection, when appropriate to the problem
• Collaborate across Data Science, Data Engineering, Application Engineering, Product, R&D, and Customer Experience teams

What they're looking for:

• We seek strong quantitative reasoning, Python and SQL proficiency, and a self-driven curiosity to learn new technologies and own complex challenges
• Relevant professional experience in data science, scientific computing, engineering analytics, or related quantitative work
• Candidates with an advanced degree and substantial applied research or project experience will also be considered
• Strong Python and SQL skills, including experience developing maintainable, modular code beyond exploratory notebooks and working with complex, real-world datasets
• Strong quantitative and analytical problem-solving skills, including comfort reasoning about equations, assumptions, data relationships, and statistical results
• Working knowledge of statistics, including distributions, descriptive statistics, regression, and statistical validation
• Experience investigating messy or heterogeneous datasets, identifying data-quality issues, and developing defensible analytical approaches
• Familiarity with collaborative software-development practices such as Git, code review, testing, and documentation
• Strong initiative and demonstrated ability to learn unfamiliar technical subjects, ask effective questions, seek out relevant expertise, and progressively take ownership of new problems
• Ability to communicate analytical approaches, assumptions, and results clearly to technical and non-technical colleagues
• BS or MS degree in Engineering, Physics, Applied Mathematics, Data Science, or another related quantitative scientific or technical discipline
• Experience working with energy, utilities, industrial, environmental, or emissions-related data, including greenhouse-gas or methane analytics

Benefits:

• Hybrid work arrangement in Houston, TX
• Continuous learning and discovery through collaborative work