Data Scientist

Talascend is currently seeking a Data Scientist for a contract opportunity with our client in Greenville, South Carolina.

Overview

The Data Scientist will contribute to data analysis, model development, and strategic planning activities supporting energy operations and business optimization. The role involves working with enterprise data, developing AI/ML models, and collaborating with cross-functional teams to drive data-driven decision-making.

Responsibilities

• Analyze quality data from multiple enterprise systems to identify patterns, gaps, and opportunities for data-driven improvements
• Work with Program Managers and Operations leaders to define relevant data assets and specify how data should be accessed and used
• Transform structured and unstructured datasets into actionable insights
• Develop and validate machine learning models supporting demand forecasting, scenario modeling, and predictive use cases
• Document analytical findings, model performance, and data definitions for transparency and reproducibility
• Collaborate with data engineers to build and maintain Python-based data pipelines for ETL, model training, and automation workflows
• Design and execute scenario planning models to test business assumptions and evaluate outcomes
• Track project execution data across project management systems, linking planning assumptions to actual performance
• Review and analyze existing dashboards, models, and data pipelines to understand design patterns and optimize reporting and modeling assets
• Translate complex data findings into clear insights for technical and non-technical audiences
• Support the Operations team with data analysis-based reporting and KPI delivery across global business lines
• Collaborate with cross-functional teams to ensure data requirements are correctly implemented and understood
• Stay current with AI, ML, and data science advancements to propose innovative solutions

Qualifications

• Bachelor's degree in a relevant field
• Proven experience in data analysis and data science
• Demonstrated ability to perform the duties of this position through relevant experience, training, or education
• Strong proficiency in Python (pandas, numpy, scikit-learn, scipy, object-oriented programming)
• Experience with scenario planning, ML frameworks, and model evaluation metrics (R², MAE, RMSE, cross-validation)
• Proficiency in SQL querying, data manipulation, and interpreting complex queries
• Understanding of statistical modeling, hypothesis testing, and experimental design
• Ability to explore enterprise datasets and identify patterns, gaps, and opportunities
• Experience merging data from various enterprise sources (SAP, Salesforce, Databricks, ERP/CRM systems)
• Knowledge of data modeling concepts, forecasting, and predictive analytics
• Familiarity with Large Language Models and prompt engineering techniques
• Ability to review existing dashboards, models, and reports to understand design patterns and data flows
• Excellent communication and collaboration skills with stakeholder engagement experience
• Strong problem-solving abilities with attention to detail and scientific rigor
• Technical curiosity and a collaborative mindset

Preferred Qualifications

• Experience with TensorFlow, PyTorch, neural networks, or deep learning applications
• Knowledge of model versioning, experiment tracking, and deployment tools (MLflow, Weights & Biases)
• Experience with cloud platforms such as Azure, AWS, or GCP
• Familiarity with advanced LLM applications like fine-tuning and Retrieval-Augmented Generation (RAG)
• Understanding of data governance principles and responsible AI practices
• Hands-on experience with enterprise systems like SAP, Salesforce, or Databricks from a data consumption perspective