Data Science Analyst Contract Duration: 12+ months with the possibility of extension or conversion to full-time Location: Hybrid in Princeton, NJ 08540 (3 days onsite per week, 2 remote) Estimated Hourly Rate: $40-$56 per hour on W2 contract Work Authorization: Must have proper work authorization without need for sponsorship.We do not accommodate C2C (corp-to-corp) arrangements under any circumstances. All contractors must be on a direct W2 with our company. Summary: The Data Scientist will play a key role in supporting a wide range of data science initiatives, enabling the Commercial Analytics team to operate more efficiently. By leveraging advanced technologies and modern analytical techniques, this role will help the team to streamline processes, drive innovation, and enhance overall decision-making capabilities. Responsibilities: • Collect, clean, and preprocess large datasets to ensure high-quality data for quantitative analysis including AI applications. • Develop and implement machine learning models for predictive analytics, recommendation systems, anomaly detection, and other AI-driven insights. • Implement solutions that improve efficiency of team activities. • Analyze and interpret complex data structures to derive meaningful business insights. • Collaborate with cross-functional teams, including software engineers, data engineers, and business analysts, to integrate AI solutions into group workflows. • Optimize and fine-tune AI models to enhance accuracy, efficiency, and scalability. • Stay up to date with the latest advancements in AI, machine learning, and data science technologies. • Create data visualizations and dashboards to communicate findings to stakeholders effectively. • Document methodologies, processes, and findings to maintain transparency and reproducibility. Minimum Requirements • Bachelor's degree, Master's degree preferred, in data science, computer science, quantitative finance, statistics, or mathematics • 3+ years of work experience in data analysis, machine learning, and AI applications • High level of proficiency in SQL and quantitative programming (Python, R, MATLAB). Experienced in dealing with large data sets. • Experience with AI/ML frameworks such as TensorFlow, PyTorch, Scikit-Learn. • Strong knowledge of data visualization tools such as Tableau, Power BI, or Matplotlib. • Familiarity with cloud computing platforms such as AWS, Azure, or Google Cloud. • Strong communication skills. Ability to translate complex data into actionable insights. • Experience in financial data analysis in the utility industry (profit/loss, forecasting, pricing, costs) Preferred Qualifications: • Experience with Natural Language Processing (NLP) or Computer Vision. • Knowledge of big data technologies such as Spark, Hadoop, or Databricks. • Exposure to deep learning techniques and neural networks. • Understanding of MLOps principles and deployment of AI models in production environments.