Python Developer

Duration: 06 Months Contract (Possibility of Extension) Location: Houston, TX (Hybrid) Payrate: $50-55 per hour on w2, without benefits Interview Rounds Round 1 Skills Assessment: via Teams Round 2 Skills Assessment: In person, technical assessment. Candidate must bring their own laptop for onsite test Job Description Key accountabilities You will build direct relationships with key analysts and commercial stakeholders, understand their business requirements and immediate goals, and build effective technical solutions based on their guidance. Build efficient, resilient and innovative solutions using modern data analytics technologies (including Dataiku, Power BI and Plotly Dash), that enable analysts, inform decision making and drive revenue generation. Design and build scalable, reusable components and frameworks in-line with mandated architectures. Bachelor’s degree in computer science or a related technical field (e.g., Software Engineering, Electrical Engineering, Mathematics, Physics). Essential experience and job requirements Fluent English knowledge and ability to communicate effectively, both verbally and in writing. Demonstrated experience with Python programming for data analysis, including working knowledge of libraries such as pandas , NumPy , and Jupyter . Experience in Object-Oriented Programming, ability to design intuitive, maintainable classes while effectively utilizing design patterns. Working knowledge of SQL and relational database systems. Familiarity with cloud computing concepts, preferably AWS. Exposure to data visualization tools and frameworks (e.g., Plotly, Dash, Power BI). Strong analytical, reasoning, and mathematical skills. Familiarity with energy markets (e.g. oil, natural gas, low-carbon, LNG, or power). Exposure to time series forecasting, econometrics, or optimization techniques. Experience working with data science platforms such as Dataiku. Interest in UX design and end-user-focused development. Industry experience of large-scale data analysis and predictive modelling, preferably in an investment bank, hedge fund or energy major. Familiarity with the scientific Python stack, including scikit-learn , SciPy , and statsmodels . #J-18808-Ljbffr