Job Description

Data Scientist

Our client is seeking a talented and motivated Data Scientist to join their dynamic team. The Data Scientist will leverage advanced analytics, machine learning, and statistical modeling to support data-driven decision making across the organization. This role will play a key part in extracting insights from complex datasets to improve operational efficiency, customer experience, and strategic planning within the energy sector.

Key Responsibilities

• Apply a consultative approach to data science, partnering with stakeholders to identify business problems, recommend tailored analytical solutions, and guide decision-making throughout project lifecycles.
• Analyze large and diverse datasets to identify trends, patterns, and opportunities for improvement within operations.
• Design, develop, and deploy predictive models and machine learning algorithms to solve business challenges.
• Collaborate with cross-functional teams, including IT, engineering, and business units, to understand data needs and deliver actionable insights.
• Visualize data findings and communicate results clearly to both technical and non-technical stakeholders.
• Support the implementation of data governance standards and ensure the integrity and security of data.
• Stay updated on emerging technologies and best practices in data science and the energy industry.

Qualifications

• Bachelors or Masters degree in Data Science, Computer Science, Statistics, Mathematics, or related field.
• 2–5+ years of experience as a Data Scientist, ML Engineer, or similar role.
• Strong proficiency in Python (pandas, scikit‑learn, NumPy, SciPy, TensorFlow/PyTorch optional).
• Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow).
• Experience working with data warehouses, SQL databases, and cloud platforms (AWS, Azure, GCP).
• Familiarity with visualization tools such as Tableau, Power BI, or matplotlib.
• Experience with statistical modeling, forecasting, and optimization.
• Experience in the energy or utilities industry.
• Knowledge of cloud platforms (e.g., Azure, AWS, Google Cloud) and big data technologies (e.g., Hadoop, Spark).
• Exposure to MLOps practices and production model deployment.

This is a hybrid position based in San Antonio TX.